diff --git a/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/multistream/README.md b/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/multistream/README.md index 444a630d..f9c6ea70 100644 --- a/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/multistream/README.md +++ b/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/multistream/README.md @@ -19,7 +19,7 @@ pip install -U cmind cm rm cache -f -cm pull repo mlcommons@mlperf-automations --checkout=225220c7d9bb7e66e5b9a1e1ebfc3e0180fbd094 +cm pull repo mlcommons@mlperf-automations --checkout=a90475d2de72bf0622cebe8d5ca8eb8c9d872fbd cm run script \ --tags=app,mlperf,inference,generic,_nvidia,_retinanet,_tensorrt,_cuda,_valid,_r4.1-dev_default,_multistream \ @@ -71,7 +71,7 @@ cm run script \ --env.CM_DOCKER_REUSE_EXISTING_CONTAINER=yes \ --env.CM_DOCKER_DETACHED_MODE=yes \ --env.CM_MLPERF_INFERENCE_RESULTS_DIR_=/home/arjun/gh_action_results/valid_results \ - --env.CM_DOCKER_CONTAINER_ID=e891b1c381b6 \ + --env.CM_DOCKER_CONTAINER_ID=f77641321894 \ --env.CM_MLPERF_LOADGEN_COMPLIANCE_TEST=TEST01 \ --add_deps_recursive.compiler.tags=gcc \ --add_deps_recursive.coco2014-original.tags=_full \ @@ -129,7 +129,7 @@ Platform: RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config Model Precision: int8 ### Accuracy Results -`mAP`: `37.356`, Required accuracy for closed division `>= 37.1745` +`mAP`: `37.327`, Required accuracy for closed division `>= 37.1745` ### Performance Results -`Samples per query`: `5654438.0` +`Samples per query`: `5623507.0` diff --git a/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/multistream/accuracy_console.out b/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/multistream/accuracy_console.out index 33c1d739..4d31cdaa 100644 --- a/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/multistream/accuracy_console.out +++ b/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/multistream/accuracy_console.out @@ -1,8 +1,8 @@ -[2024-12-23 02:36:38,287 main.py:229 INFO] Detected system ID: KnownSystem.RTX4090x2 -[2024-12-23 02:36:38,369 harness.py:249 INFO] The harness will load 2 plugins: ['build/plugins/NMSOptPlugin/libnmsoptplugin.so', 'build/plugins/retinanetConcatPlugin/libretinanetconcatplugin.so'] -[2024-12-23 02:36:38,369 generate_conf_files.py:107 INFO] Generated measurements/ entries for RTX4090x2_TRT/retinanet/MultiStream -[2024-12-23 02:36:38,369 __init__.py:46 INFO] Running command: ./build/bin/harness_default --plugins="build/plugins/NMSOptPlugin/libnmsoptplugin.so,build/plugins/retinanetConcatPlugin/libretinanetconcatplugin.so" --logfile_outdir="/cm-mount/home/arjun/gh_action_results/valid_results/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/multistream/accuracy" --logfile_prefix="mlperf_log_" --performance_sample_count=64 --test_mode="AccuracyOnly" --gpu_copy_streams=1 --gpu_inference_streams=1 --use_deque_limit=true --gpu_batch_size=2 --map_path="data_maps/open-images-v6-mlperf/val_map.txt" --mlperf_conf_path="/home/cmuser/CM/repos/local/cache/5860c00d55d14786/inference/mlperf.conf" --tensor_path="build/preprocessed_data/open-images-v6-mlperf/validation/Retinanet/int8_linear" --use_graphs=true --user_conf_path="/home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/c44de86dadc4420199ad25d6fa563275.conf" --gpu_engines="./build/engines/RTX4090x2/retinanet/MultiStream/retinanet-MultiStream-gpu-b2-int8.lwis_k_99_MaxP.plan" --max_dlas=0 --scenario MultiStream --model retinanet --response_postprocess openimageeffnms -[2024-12-23 02:36:38,369 __init__.py:53 INFO] Overriding Environment +[2024-12-25 01:40:51,607 main.py:229 INFO] Detected system ID: KnownSystem.RTX4090x2 +[2024-12-25 01:40:51,689 harness.py:249 INFO] The harness will load 2 plugins: ['build/plugins/NMSOptPlugin/libnmsoptplugin.so', 'build/plugins/retinanetConcatPlugin/libretinanetconcatplugin.so'] +[2024-12-25 01:40:51,689 generate_conf_files.py:107 INFO] Generated measurements/ entries for RTX4090x2_TRT/retinanet/MultiStream +[2024-12-25 01:40:51,689 __init__.py:46 INFO] Running command: ./build/bin/harness_default --plugins="build/plugins/NMSOptPlugin/libnmsoptplugin.so,build/plugins/retinanetConcatPlugin/libretinanetconcatplugin.so" --logfile_outdir="/cm-mount/home/arjun/gh_action_results/valid_results/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/multistream/accuracy" --logfile_prefix="mlperf_log_" --performance_sample_count=64 --test_mode="AccuracyOnly" --gpu_copy_streams=1 --gpu_inference_streams=1 --use_deque_limit=true --gpu_batch_size=2 --map_path="data_maps/open-images-v6-mlperf/val_map.txt" --mlperf_conf_path="/home/cmuser/CM/repos/local/cache/5860c00d55d14786/inference/mlperf.conf" --tensor_path="build/preprocessed_data/open-images-v6-mlperf/validation/Retinanet/int8_linear" --use_graphs=true --user_conf_path="/home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/00cdca2a511c4f33bad6658d0557db67.conf" --gpu_engines="./build/engines/RTX4090x2/retinanet/MultiStream/retinanet-MultiStream-gpu-b2-int8.lwis_k_99_MaxP.plan" --max_dlas=0 --scenario MultiStream --model retinanet --response_postprocess openimageeffnms +[2024-12-25 01:40:51,689 __init__.py:53 INFO] Overriding Environment benchmark : Benchmark.Retinanet buffer_manager_thread_count : 0 data_dir : /home/cmuser/CM/repos/local/cache/4db00c74da1e44c8/data @@ -12,7 +12,7 @@ gpu_copy_streams : 1 gpu_inference_streams : 1 input_dtype : int8 input_format : linear -log_dir : /home/cmuser/CM/repos/local/cache/94a57f78972843c6/repo/closed/NVIDIA/build/logs/2024.12.23-02.36.37 +log_dir : /home/cmuser/CM/repos/local/cache/94a57f78972843c6/repo/closed/NVIDIA/build/logs/2024.12.25-01.40.50 map_path : data_maps/open-images-v6-mlperf/val_map.txt mlperf_conf_path : /home/cmuser/CM/repos/local/cache/5860c00d55d14786/inference/mlperf.conf multi_stream_expected_latency_ns : 0 @@ -26,7 +26,7 @@ tensor_path : build/preprocessed_data/open-images-v6-mlperf/validation/Retinanet test_mode : AccuracyOnly use_deque_limit : True use_graphs : True -user_conf_path : /home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/c44de86dadc4420199ad25d6fa563275.conf +user_conf_path : /home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/00cdca2a511c4f33bad6658d0557db67.conf system_id : RTX4090x2 config_name : RTX4090x2_retinanet_MultiStream workload_setting : WorkloadSetting(HarnessType.LWIS, AccuracyTarget.k_99, PowerSetting.MaxP) @@ -40,28 +40,28 @@ power_limit : None cpu_freq : None &&&& RUNNING Default_Harness # ./build/bin/harness_default [I] mlperf.conf path: /home/cmuser/CM/repos/local/cache/5860c00d55d14786/inference/mlperf.conf -[I] user.conf path: /home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/c44de86dadc4420199ad25d6fa563275.conf +[I] user.conf path: /home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/00cdca2a511c4f33bad6658d0557db67.conf Creating QSL. Finished Creating QSL. Setting up SUT. -[I] [TRT] Loaded engine size: 72 MiB -[I] [TRT] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +6, GPU +10, now: CPU 125, GPU 881 (MiB) -[I] [TRT] [MemUsageChange] Init cuDNN: CPU +2, GPU +10, now: CPU 127, GPU 891 (MiB) +[I] [TRT] Loaded engine size: 73 MiB +[I] [TRT] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +6, GPU +10, now: CPU 126, GPU 881 (MiB) +[I] [TRT] [MemUsageChange] Init cuDNN: CPU +2, GPU +10, now: CPU 128, GPU 891 (MiB) [I] [TRT] [MemUsageChange] TensorRT-managed allocation in engine deserialization: CPU +0, GPU +68, now: CPU 0, GPU 68 (MiB) [I] Device:0.GPU: [0] ./build/engines/RTX4090x2/retinanet/MultiStream/retinanet-MultiStream-gpu-b2-int8.lwis_k_99_MaxP.plan has been successfully loaded. -[I] [TRT] Loaded engine size: 72 MiB +[I] [TRT] Loaded engine size: 73 MiB [W] [TRT] Using an engine plan file across different models of devices is not recommended and is likely to affect performance or even cause errors. -[I] [TRT] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +6, GPU +10, now: CPU 159, GPU 624 (MiB) -[I] [TRT] [MemUsageChange] Init cuDNN: CPU +1, GPU +10, now: CPU 160, GPU 634 (MiB) +[I] [TRT] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +6, GPU +10, now: CPU 161, GPU 624 (MiB) +[I] [TRT] [MemUsageChange] Init cuDNN: CPU +1, GPU +10, now: CPU 162, GPU 634 (MiB) [I] [TRT] [MemUsageChange] TensorRT-managed allocation in engine deserialization: CPU +0, GPU +69, now: CPU 0, GPU 137 (MiB) [I] Device:1.GPU: [0] ./build/engines/RTX4090x2/retinanet/MultiStream/retinanet-MultiStream-gpu-b2-int8.lwis_k_99_MaxP.plan has been successfully loaded. [E] [TRT] 3: [runtime.cpp::~Runtime::401] Error Code 3: API Usage Error (Parameter check failed at: runtime/rt/runtime.cpp::~Runtime::401, condition: mEngineCounter.use_count() == 1 Destroying a runtime before destroying deserialized engines created by the runtime leads to undefined behavior.) -[I] [TRT] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +0, GPU +8, now: CPU 88, GPU 893 (MiB) -[I] [TRT] [MemUsageChange] Init cuDNN: CPU +0, GPU +8, now: CPU 88, GPU 901 (MiB) +[I] [TRT] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +0, GPU +8, now: CPU 89, GPU 893 (MiB) +[I] [TRT] [MemUsageChange] Init cuDNN: CPU +1, GPU +8, now: CPU 90, GPU 901 (MiB) [I] [TRT] [MemUsageChange] TensorRT-managed allocation in IExecutionContext creation: CPU +1, GPU +1528, now: CPU 1, GPU 1665 (MiB) -[I] [TRT] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +0, GPU +8, now: CPU 89, GPU 636 (MiB) -[I] [TRT] [MemUsageChange] Init cuDNN: CPU +0, GPU +8, now: CPU 89, GPU 644 (MiB) -[I] [TRT] [MemUsageChange] TensorRT-managed allocation in IExecutionContext creation: CPU +0, GPU +1528, now: CPU 1, GPU 3193 (MiB) +[I] [TRT] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +0, GPU +8, now: CPU 90, GPU 636 (MiB) +[I] [TRT] [MemUsageChange] Init cuDNN: CPU +0, GPU +8, now: CPU 90, GPU 644 (MiB) +[I] [TRT] [MemUsageChange] TensorRT-managed allocation in IExecutionContext creation: CPU +0, GPU +1527, now: CPU 1, GPU 3192 (MiB) [I] Start creating CUDA graphs [I] Capture 2 CUDA graphs [I] Capture 2 CUDA graphs @@ -69,7 +69,7 @@ Setting up SUT. [I] Creating batcher thread: 0 EnableBatcherThreadPerDevice: false Finished setting up SUT. Starting warmup. Running for a minimum of 5 seconds. -Finished warmup. Ran for 5.14292s. +Finished warmup. Ran for 5.14343s. Starting running actual test. No warnings encountered during test. @@ -77,34 +77,34 @@ No warnings encountered during test. No errors encountered during test. Finished running actual test. Device Device:0.GPU processed: - 6195 batches of size 2 + 6196 batches of size 2 Memcpy Calls: 0 PerSampleCudaMemcpy Calls: 0 - BatchedCudaMemcpy Calls: 6195 + BatchedCudaMemcpy Calls: 6196 Device Device:1.GPU processed: - 6197 batches of size 2 + 6196 batches of size 2 Memcpy Calls: 0 PerSampleCudaMemcpy Calls: 0 - BatchedCudaMemcpy Calls: 6197 + BatchedCudaMemcpy Calls: 6196 &&&& PASSED Default_Harness # ./build/bin/harness_default -[2024-12-23 02:37:18,118 run_harness.py:166 INFO] Result: Accuracy run detected. -[2024-12-23 02:37:18,118 __init__.py:46 INFO] Running command: python3 /home/cmuser/CM/repos/local/cache/94a57f78972843c6/repo/closed/NVIDIA/build/inference/vision/classification_and_detection/tools/accuracy-openimages.py --mlperf-accuracy-file /cm-mount/home/arjun/gh_action_results/valid_results/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/multistream/accuracy/mlperf_log_accuracy.json --openimages-dir /home/cmuser/CM/repos/local/cache/4db00c74da1e44c8/preprocessed_data/open-images-v6-mlperf --output-file build/retinanet-results.json +[2024-12-25 01:41:30,299 run_harness.py:166 INFO] Result: Accuracy run detected. +[2024-12-25 01:41:30,299 __init__.py:46 INFO] Running command: python3 /home/cmuser/CM/repos/local/cache/94a57f78972843c6/repo/closed/NVIDIA/build/inference/vision/classification_and_detection/tools/accuracy-openimages.py --mlperf-accuracy-file /cm-mount/home/arjun/gh_action_results/valid_results/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/multistream/accuracy/mlperf_log_accuracy.json --openimages-dir /home/cmuser/CM/repos/local/cache/4db00c74da1e44c8/preprocessed_data/open-images-v6-mlperf --output-file build/retinanet-results.json loading annotations into memory... -Done (t=0.52s) +Done (t=0.53s) creating index... index created! Loading and preparing results... -DONE (t=17.77s) +DONE (t=17.92s) creating index... index created! Running per image evaluation... Evaluate annotation type *bbox* -DONE (t=133.59s). +DONE (t=133.92s). Accumulating evaluation results... -DONE (t=31.87s). - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.374 +DONE (t=32.42s). + Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.373 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.522 - Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.404 + Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.403 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.022 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.125 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.413 @@ -112,9 +112,9 @@ DONE (t=31.87s). Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.599 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.628 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.082 - Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.345 - Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.678 -mAP=37.356% + Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.344 + Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.677 +mAP=37.327% ======================== Result summaries: ======================== diff --git a/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/multistream/cm-deps.mmd b/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/multistream/cm-deps.mmd index 04612c79..6e0cb54d 100644 --- a/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/multistream/cm-deps.mmd +++ b/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/multistream/cm-deps.mmd @@ -14,19 +14,19 @@ graph TD get-generic-python-lib,94b62a682bc44791_(_package.numpy_) --> get,python3 get-cuda-devices,7a3ede4d3558427a_(_with-pycuda_) --> get,generic-python-lib,_package.numpy app-mlperf-inference,d775cac873ee4231_(_nvidia,_retinanet,_tensorrt,_cuda,_valid,_r4.1-dev_default,_multistream_) --> get,cuda-devices,_with-pycuda - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_retinanet,_multistream,_tensorrt,_cuda,_rtx_4090_) --> detect,os + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_multistream,_cuda,_retinanet,_rtx_4090_) --> detect,os detect-cpu,586c8a43320142f7 --> detect,os - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_retinanet,_multistream,_tensorrt,_cuda,_rtx_4090_) --> detect,cpu - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_retinanet,_multistream,_tensorrt,_cuda,_rtx_4090_) --> get,sys-utils-cm - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_retinanet,_multistream,_tensorrt,_cuda,_rtx_4090_) --> get,mlperf,inference,nvidia,scratch,space + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_multistream,_cuda,_retinanet,_rtx_4090_) --> detect,cpu + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_multistream,_cuda,_retinanet,_rtx_4090_) --> get,sys-utils-cm + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_multistream,_cuda,_retinanet,_rtx_4090_) --> get,mlperf,inference,nvidia,scratch,space get-generic-python-lib,94b62a682bc44791_(_mlperf_logging_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_retinanet,_multistream,_tensorrt,_cuda,_rtx_4090_) --> get,generic-python-lib,_mlperf_logging - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_retinanet,_multistream,_tensorrt,_cuda,_rtx_4090_) --> get,dataset,original,openimages,_validation,_full,_custom-annotations - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_retinanet,_multistream,_tensorrt,_cuda,_rtx_4090_) --> get,dataset,original,openimages,_calibration - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_retinanet,_multistream,_tensorrt,_cuda,_rtx_4090_) --> get,mlcommons,inference,src - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_retinanet,_multistream,_tensorrt,_cuda,_rtx_4090_) --> get,nvidia,mlperf,inference,common-code,_mlcommons + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_multistream,_cuda,_retinanet,_rtx_4090_) --> get,generic-python-lib,_mlperf_logging + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_multistream,_cuda,_retinanet,_rtx_4090_) --> get,dataset,original,openimages,_validation,_full,_custom-annotations + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_multistream,_cuda,_retinanet,_rtx_4090_) --> get,dataset,original,openimages,_calibration + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_multistream,_cuda,_retinanet,_rtx_4090_) --> get,mlcommons,inference,src + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_multistream,_cuda,_retinanet,_rtx_4090_) --> get,nvidia,mlperf,inference,common-code,_mlcommons pull-git-repo,c23132ed65c4421d --> detect,os - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_retinanet,_multistream,_tensorrt,_cuda,_rtx_4090_) --> pull,git,repo + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_multistream,_cuda,_retinanet,_rtx_4090_) --> pull,git,repo generate-mlperf-inference-user-conf,3af4475745964b93 --> detect,os detect-cpu,586c8a43320142f7 --> detect,os generate-mlperf-inference-user-conf,3af4475745964b93 --> detect,cpu @@ -34,67 +34,67 @@ graph TD generate-mlperf-inference-user-conf,3af4475745964b93 --> get,mlcommons,inference,src get-mlperf-inference-sut-configs,c2fbf72009e2445b --> get,cache,dir,_name.mlperf-inference-sut-configs generate-mlperf-inference-user-conf,3af4475745964b93 --> get,sut,configs - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_retinanet,_multistream,_tensorrt,_cuda,_rtx_4090_) --> generate,user-conf,mlperf,inference + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_multistream,_cuda,_retinanet,_rtx_4090_) --> generate,user-conf,mlperf,inference get-generic-python-lib,94b62a682bc44791_(_package.pycuda_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_retinanet,_multistream,_tensorrt,_cuda,_rtx_4090_) --> get,generic-python-lib,_package.pycuda - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_retinanet,_multistream,_tensorrt,_cuda,_rtx_4090_) --> get,nvidia,mitten - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_retinanet,_multistream,_tensorrt,_cuda,_rtx_4090_) --> get,cuda,_cudnn - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_retinanet,_multistream,_tensorrt,_cuda,_rtx_4090_) --> get,tensorrt - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_retinanet,_multistream,_tensorrt,_cuda,_rtx_4090_) --> build,nvidia,inference,server,_mlcommons - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_retinanet,_multistream,_tensorrt,_cuda,_batch_size.2,_v4.1-dev_) --> detect,os + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_multistream,_cuda,_retinanet,_rtx_4090_) --> get,generic-python-lib,_package.pycuda + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_multistream,_cuda,_retinanet,_rtx_4090_) --> get,nvidia,mitten + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_multistream,_cuda,_retinanet,_rtx_4090_) --> get,cuda,_cudnn + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_multistream,_cuda,_retinanet,_rtx_4090_) --> get,tensorrt + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_multistream,_cuda,_retinanet,_rtx_4090_) --> build,nvidia,inference,server,_mlcommons + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_multistream,_cuda,_retinanet,_batch_size.2,_v4.1-dev_) --> detect,os detect-cpu,586c8a43320142f7 --> detect,os - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_retinanet,_multistream,_tensorrt,_cuda,_batch_size.2,_v4.1-dev_) --> detect,cpu - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_retinanet,_multistream,_tensorrt,_cuda,_batch_size.2,_v4.1-dev_) --> get,sys-utils-cm - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_retinanet,_multistream,_tensorrt,_cuda,_batch_size.2,_v4.1-dev_) --> get,mlperf,inference,nvidia,scratch,space,_version.4_0 + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_multistream,_cuda,_retinanet,_batch_size.2,_v4.1-dev_) --> detect,cpu + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_multistream,_cuda,_retinanet,_batch_size.2,_v4.1-dev_) --> get,sys-utils-cm + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_multistream,_cuda,_retinanet,_batch_size.2,_v4.1-dev_) --> get,mlperf,inference,nvidia,scratch,space,_version.4_0 get-generic-python-lib,94b62a682bc44791_(_mlperf_logging_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_retinanet,_multistream,_tensorrt,_cuda,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_mlperf_logging - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_retinanet,_multistream,_tensorrt,_cuda,_batch_size.2,_v4.1-dev_) --> get,dataset,original,openimages,_validation,_full,_custom-annotations - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_retinanet,_multistream,_tensorrt,_cuda,_batch_size.2,_v4.1-dev_) --> get,dataset,original,openimages,_calibration - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_retinanet,_multistream,_tensorrt,_cuda,_batch_size.2,_v4.1-dev_) --> get,mlcommons,inference,src - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_retinanet,_multistream,_tensorrt,_cuda,_batch_size.2,_v4.1-dev_) --> get,nvidia,mlperf,inference,common-code,_mlcommons + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_multistream,_cuda,_retinanet,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_mlperf_logging + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_multistream,_cuda,_retinanet,_batch_size.2,_v4.1-dev_) --> get,dataset,original,openimages,_validation,_full,_custom-annotations + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_multistream,_cuda,_retinanet,_batch_size.2,_v4.1-dev_) --> get,dataset,original,openimages,_calibration + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_multistream,_cuda,_retinanet,_batch_size.2,_v4.1-dev_) --> get,mlcommons,inference,src + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_multistream,_cuda,_retinanet,_batch_size.2,_v4.1-dev_) --> get,nvidia,mlperf,inference,common-code,_mlcommons pull-git-repo,c23132ed65c4421d --> detect,os - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_retinanet,_multistream,_tensorrt,_cuda,_batch_size.2,_v4.1-dev_) --> pull,git,repo + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_multistream,_cuda,_retinanet,_batch_size.2,_v4.1-dev_) --> pull,git,repo get-generic-python-lib,94b62a682bc44791_(_package.pycuda_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_retinanet,_multistream,_tensorrt,_cuda,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_package.pycuda - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_retinanet,_multistream,_tensorrt,_cuda,_batch_size.2,_v4.1-dev_) --> get,nvidia,mitten - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_retinanet,_multistream,_tensorrt,_cuda,_batch_size.2,_v4.1-dev_) --> get,cuda,_cudnn - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_retinanet,_multistream,_tensorrt,_cuda,_batch_size.2,_v4.1-dev_) --> get,tensorrt - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_retinanet,_multistream,_tensorrt,_cuda,_batch_size.2,_v4.1-dev_) --> build,nvidia,inference,server,_mlcommons - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_retinanet,_multistream,_tensorrt,_cuda,_batch_size.2,_v4.1-dev_) --> reproduce,mlperf,inference,nvidia,harness,_preprocess_data,_retinanet,_tensorrt,_cuda,_v4.1-dev - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_retinanet,_multistream,_tensorrt,_cuda,_batch_size.2,_v4.1-dev_) --> reproduce,mlperf,inference,nvidia,harness,_download_model,_retinanet,_tensorrt,_cuda,_v4.1-dev - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_retinanet,_multistream,_tensorrt,_cuda,_batch_size.2,_v4.1-dev_) --> reproduce,mlperf,inference,nvidia,harness,_calibrate,_retinanet,_tensorrt,_cuda,_v4.1-dev + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_multistream,_cuda,_retinanet,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_package.pycuda + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_multistream,_cuda,_retinanet,_batch_size.2,_v4.1-dev_) --> get,nvidia,mitten + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_multistream,_cuda,_retinanet,_batch_size.2,_v4.1-dev_) --> get,cuda,_cudnn + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_multistream,_cuda,_retinanet,_batch_size.2,_v4.1-dev_) --> get,tensorrt + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_multistream,_cuda,_retinanet,_batch_size.2,_v4.1-dev_) --> build,nvidia,inference,server,_mlcommons + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_multistream,_cuda,_retinanet,_batch_size.2,_v4.1-dev_) --> reproduce,mlperf,inference,nvidia,harness,_preprocess_data,_tensorrt,_cuda,_retinanet,_v4.1-dev + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_multistream,_cuda,_retinanet,_batch_size.2,_v4.1-dev_) --> reproduce,mlperf,inference,nvidia,harness,_download_model,_tensorrt,_cuda,_retinanet,_v4.1-dev + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_multistream,_cuda,_retinanet,_batch_size.2,_v4.1-dev_) --> reproduce,mlperf,inference,nvidia,harness,_calibrate,_tensorrt,_cuda,_retinanet,_v4.1-dev get-generic-python-lib,94b62a682bc44791_(_Pillow_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_retinanet,_multistream,_tensorrt,_cuda,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_Pillow + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_multistream,_cuda,_retinanet,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_Pillow get-generic-python-lib,94b62a682bc44791_(_opencv-python_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_retinanet,_multistream,_tensorrt,_cuda,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_opencv-python + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_multistream,_cuda,_retinanet,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_opencv-python get-generic-python-lib,94b62a682bc44791_(_numpy_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_retinanet,_multistream,_tensorrt,_cuda,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_numpy + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_multistream,_cuda,_retinanet,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_numpy get-generic-python-lib,94b62a682bc44791_(_pycocotools_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_retinanet,_multistream,_tensorrt,_cuda,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_pycocotools + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_multistream,_cuda,_retinanet,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_pycocotools get-generic-python-lib,94b62a682bc44791_(_onnx-graphsurgeon_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_retinanet,_multistream,_tensorrt,_cuda,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_onnx-graphsurgeon + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_multistream,_cuda,_retinanet,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_onnx-graphsurgeon get-generic-python-lib,94b62a682bc44791_(_package.onnx_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_retinanet,_multistream,_tensorrt,_cuda,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_package.onnx + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_multistream,_cuda,_retinanet,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_package.onnx get-generic-python-lib,94b62a682bc44791_(_package.sympy_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_retinanet,_multistream,_tensorrt,_cuda,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_package.sympy - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_retinanet,_multistream,_tensorrt,_cuda,_batch_size.2,_v4.1-dev_) --> save,mlperf,inference,state - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_retinanet,_multistream,_tensorrt,_cuda,_rtx_4090_) --> reproduce,mlperf,inference,nvidia,harness,_build_engine,_retinanet,_multistream,_tensorrt,_cuda,_batch_size.2,_v4.1-dev - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_retinanet,_multistream,_tensorrt,_cuda,_rtx_4090_) --> reproduce,mlperf,inference,nvidia,harness,_preprocess_data,_retinanet,_tensorrt,_cuda,_v4.1-dev + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_multistream,_cuda,_retinanet,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_package.sympy + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_multistream,_cuda,_retinanet,_batch_size.2,_v4.1-dev_) --> save,mlperf,inference,state + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_multistream,_cuda,_retinanet,_rtx_4090_) --> reproduce,mlperf,inference,nvidia,harness,_build_engine,_tensorrt,_multistream,_cuda,_retinanet,_batch_size.2,_v4.1-dev + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_multistream,_cuda,_retinanet,_rtx_4090_) --> reproduce,mlperf,inference,nvidia,harness,_preprocess_data,_tensorrt,_cuda,_retinanet,_v4.1-dev get-generic-python-lib,94b62a682bc44791_(_Pillow_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_retinanet,_multistream,_tensorrt,_cuda,_rtx_4090_) --> get,generic-python-lib,_Pillow + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_multistream,_cuda,_retinanet,_rtx_4090_) --> get,generic-python-lib,_Pillow get-generic-python-lib,94b62a682bc44791_(_opencv-python_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_retinanet,_multistream,_tensorrt,_cuda,_rtx_4090_) --> get,generic-python-lib,_opencv-python + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_multistream,_cuda,_retinanet,_rtx_4090_) --> get,generic-python-lib,_opencv-python get-generic-python-lib,94b62a682bc44791_(_numpy_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_retinanet,_multistream,_tensorrt,_cuda,_rtx_4090_) --> get,generic-python-lib,_numpy + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_multistream,_cuda,_retinanet,_rtx_4090_) --> get,generic-python-lib,_numpy get-generic-python-lib,94b62a682bc44791_(_pycocotools_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_retinanet,_multistream,_tensorrt,_cuda,_rtx_4090_) --> get,generic-python-lib,_pycocotools + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_multistream,_cuda,_retinanet,_rtx_4090_) --> get,generic-python-lib,_pycocotools get-generic-python-lib,94b62a682bc44791_(_onnx-graphsurgeon_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_retinanet,_multistream,_tensorrt,_cuda,_rtx_4090_) --> get,generic-python-lib,_onnx-graphsurgeon + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_multistream,_cuda,_retinanet,_rtx_4090_) --> get,generic-python-lib,_onnx-graphsurgeon get-generic-python-lib,94b62a682bc44791_(_package.onnx_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_retinanet,_multistream,_tensorrt,_cuda,_rtx_4090_) --> get,generic-python-lib,_package.onnx + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_multistream,_cuda,_retinanet,_rtx_4090_) --> get,generic-python-lib,_package.onnx get-generic-python-lib,94b62a682bc44791_(_package.sympy_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_retinanet,_multistream,_tensorrt,_cuda,_rtx_4090_) --> get,generic-python-lib,_package.sympy + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_multistream,_cuda,_retinanet,_rtx_4090_) --> get,generic-python-lib,_package.sympy detect-cpu,586c8a43320142f7 --> detect,os benchmark-program,19f369ef47084895 --> detect,cpu benchmark-program-mlperf,cfff0132a8aa4018 --> benchmark-program,program - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_retinanet,_multistream,_tensorrt,_cuda,_rtx_4090_) --> benchmark-mlperf \ No newline at end of file + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_multistream,_cuda,_retinanet,_rtx_4090_) --> benchmark-mlperf \ No newline at end of file diff --git a/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/multistream/cm-deps.png b/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/multistream/cm-deps.png index e0f46475..07ab0d5f 100644 Binary files a/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/multistream/cm-deps.png and b/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/multistream/cm-deps.png differ diff --git a/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/multistream/cm-version-info.json b/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/multistream/cm-version-info.json index 0ebc43ff..06ff5683 100644 --- a/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/multistream/cm-version-info.json +++ b/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/multistream/cm-version-info.json @@ -157,7 +157,7 @@ "script_tags": "detect-os,detect,os,info", "script_variations": "", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_retinanet,_multistream,_tensorrt,_cuda,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_multistream,_cuda,_retinanet,_rtx_4090 )" } }, { @@ -177,7 +177,7 @@ "script_tags": "detect,cpu,detect-cpu,info", "script_variations": "", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_retinanet,_multistream,_tensorrt,_cuda,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_multistream,_cuda,_retinanet,_rtx_4090 )" } }, { @@ -187,7 +187,7 @@ "script_tags": "get,sys-utils-cm", "script_variations": "", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_retinanet,_multistream,_tensorrt,_cuda,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_multistream,_cuda,_retinanet,_rtx_4090 )" } }, { @@ -197,7 +197,7 @@ "script_tags": "get,mlperf,inference,nvidia,scratch,space", "script_variations": "", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_retinanet,_multistream,_tensorrt,_cuda,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_multistream,_cuda,_retinanet,_rtx_4090 )" } }, { @@ -217,7 +217,7 @@ "script_tags": "get,install,generic,pip-package,generic-python-lib", "script_variations": "mlperf_logging", "version": "4.1.1", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_retinanet,_multistream,_tensorrt,_cuda,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_multistream,_cuda,_retinanet,_rtx_4090 )" } }, { @@ -227,7 +227,7 @@ "script_tags": "get,dataset,openimages,open-images,object-detection,original", "script_variations": "validation,full,custom-annotations", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_retinanet,_multistream,_tensorrt,_cuda,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_multistream,_cuda,_retinanet,_rtx_4090 )" } }, { @@ -237,7 +237,7 @@ "script_tags": "get,dataset,openimages,open-images,object-detection,original", "script_variations": "calibration", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_retinanet,_multistream,_tensorrt,_cuda,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_multistream,_cuda,_retinanet,_rtx_4090 )" } }, { @@ -247,7 +247,7 @@ 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+827,7 @@ "script_tags": "get,install,generic,pip-package,generic-python-lib", "script_variations": "Pillow", "version": "10.4.0", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_retinanet,_multistream,_tensorrt,_cuda,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_multistream,_cuda,_retinanet,_rtx_4090 )" } }, { @@ -847,7 +847,7 @@ "script_tags": "get,install,generic,pip-package,generic-python-lib", "script_variations": "opencv-python", "version": "4.10.0.84", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_retinanet,_multistream,_tensorrt,_cuda,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_multistream,_cuda,_retinanet,_rtx_4090 )" } }, { @@ -867,7 +867,7 @@ "script_tags": "get,install,generic,pip-package,generic-python-lib", "script_variations": "numpy", "version": "1.23.5", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_retinanet,_multistream,_tensorrt,_cuda,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_multistream,_cuda,_retinanet,_rtx_4090 )" } }, { @@ -887,7 +887,7 @@ "script_tags": "get,install,generic,pip-package,generic-python-lib", "script_variations": "pycocotools", "version": "2.0.7", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_retinanet,_multistream,_tensorrt,_cuda,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_multistream,_cuda,_retinanet,_rtx_4090 )" } }, { @@ -907,7 +907,7 @@ "script_tags": "get,install,generic,pip-package,generic-python-lib", "script_variations": "onnx-graphsurgeon", "version": "0.3.27", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_retinanet,_multistream,_tensorrt,_cuda,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_multistream,_cuda,_retinanet,_rtx_4090 )" } }, { @@ -927,7 +927,7 @@ "script_tags": "get,install,generic,pip-package,generic-python-lib", "script_variations": "package.onnx", "version": "1.14.1", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_retinanet,_multistream,_tensorrt,_cuda,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_multistream,_cuda,_retinanet,_rtx_4090 )" } }, { @@ -947,7 +947,7 @@ "script_tags": "get,install,generic,pip-package,generic-python-lib", "script_variations": "package.sympy", "version": "1.13.3", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_retinanet,_multistream,_tensorrt,_cuda,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_multistream,_cuda,_retinanet,_rtx_4090 )" } }, { @@ -987,7 +987,7 @@ "script_tags": "mlperf,benchmark-mlperf", "script_variations": "", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_retinanet,_multistream,_tensorrt,_cuda,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_multistream,_cuda,_retinanet,_rtx_4090 )" } } ] diff --git a/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/multistream/os_info.json b/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/multistream/os_info.json index 1267c343..cca704f3 100644 --- a/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/multistream/os_info.json +++ b/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/multistream/os_info.json @@ -26,5 +26,5 @@ ], "CM_HOST_PLATFORM_FLAVOR": "x86_64", "CM_HOST_PYTHON_BITS": "64", - "CM_HOST_SYSTEM_NAME": "e891b1c381b6" + "CM_HOST_SYSTEM_NAME": "f77641321894" } \ No newline at end of file diff --git a/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/multistream/performance_console.out b/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/multistream/performance_console.out index a5981dd2..16f322ba 100644 --- a/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/multistream/performance_console.out +++ b/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/multistream/performance_console.out @@ -1,8 +1,8 @@ -[2024-12-23 02:26:12,546 main.py:229 INFO] Detected system ID: KnownSystem.RTX4090x2 -[2024-12-23 02:26:12,626 harness.py:249 INFO] The harness will load 2 plugins: ['build/plugins/NMSOptPlugin/libnmsoptplugin.so', 'build/plugins/retinanetConcatPlugin/libretinanetconcatplugin.so'] -[2024-12-23 02:26:12,626 generate_conf_files.py:107 INFO] Generated measurements/ entries for RTX4090x2_TRT/retinanet/MultiStream -[2024-12-23 02:26:12,626 __init__.py:46 INFO] Running command: ./build/bin/harness_default --plugins="build/plugins/NMSOptPlugin/libnmsoptplugin.so,build/plugins/retinanetConcatPlugin/libretinanetconcatplugin.so" --logfile_outdir="/cm-mount/home/arjun/gh_action_results/valid_results/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/multistream/performance/run_1" --logfile_prefix="mlperf_log_" --performance_sample_count=64 --test_mode="PerformanceOnly" --gpu_copy_streams=1 --gpu_inference_streams=1 --use_deque_limit=true --gpu_batch_size=2 --map_path="data_maps/open-images-v6-mlperf/val_map.txt" --mlperf_conf_path="/home/cmuser/CM/repos/local/cache/5860c00d55d14786/inference/mlperf.conf" --tensor_path="build/preprocessed_data/open-images-v6-mlperf/validation/Retinanet/int8_linear" --use_graphs=true --user_conf_path="/home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/2d7ddffaece74235a135b34aa7023251.conf" --gpu_engines="./build/engines/RTX4090x2/retinanet/MultiStream/retinanet-MultiStream-gpu-b2-int8.lwis_k_99_MaxP.plan" --max_dlas=0 --scenario MultiStream --model retinanet --response_postprocess openimageeffnms -[2024-12-23 02:26:12,626 __init__.py:53 INFO] Overriding Environment +[2024-12-25 01:30:25,182 main.py:229 INFO] Detected system ID: KnownSystem.RTX4090x2 +[2024-12-25 01:30:25,265 harness.py:249 INFO] The harness will load 2 plugins: ['build/plugins/NMSOptPlugin/libnmsoptplugin.so', 'build/plugins/retinanetConcatPlugin/libretinanetconcatplugin.so'] +[2024-12-25 01:30:25,266 generate_conf_files.py:107 INFO] Generated measurements/ entries for RTX4090x2_TRT/retinanet/MultiStream +[2024-12-25 01:30:25,266 __init__.py:46 INFO] Running command: ./build/bin/harness_default --plugins="build/plugins/NMSOptPlugin/libnmsoptplugin.so,build/plugins/retinanetConcatPlugin/libretinanetconcatplugin.so" --logfile_outdir="/cm-mount/home/arjun/gh_action_results/valid_results/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/multistream/performance/run_1" --logfile_prefix="mlperf_log_" --performance_sample_count=64 --test_mode="PerformanceOnly" --gpu_copy_streams=1 --gpu_inference_streams=1 --use_deque_limit=true --gpu_batch_size=2 --map_path="data_maps/open-images-v6-mlperf/val_map.txt" --mlperf_conf_path="/home/cmuser/CM/repos/local/cache/5860c00d55d14786/inference/mlperf.conf" --tensor_path="build/preprocessed_data/open-images-v6-mlperf/validation/Retinanet/int8_linear" --use_graphs=true --user_conf_path="/home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/fdc1ee2ddd5740ac80a9fccb578452dc.conf" --gpu_engines="./build/engines/RTX4090x2/retinanet/MultiStream/retinanet-MultiStream-gpu-b2-int8.lwis_k_99_MaxP.plan" --max_dlas=0 --scenario MultiStream --model retinanet --response_postprocess openimageeffnms +[2024-12-25 01:30:25,266 __init__.py:53 INFO] Overriding Environment benchmark : Benchmark.Retinanet buffer_manager_thread_count : 0 data_dir : /home/cmuser/CM/repos/local/cache/4db00c74da1e44c8/data @@ -12,7 +12,7 @@ gpu_copy_streams : 1 gpu_inference_streams : 1 input_dtype : int8 input_format : linear -log_dir : /home/cmuser/CM/repos/local/cache/94a57f78972843c6/repo/closed/NVIDIA/build/logs/2024.12.23-02.26.11 +log_dir : /home/cmuser/CM/repos/local/cache/94a57f78972843c6/repo/closed/NVIDIA/build/logs/2024.12.25-01.30.24 map_path : data_maps/open-images-v6-mlperf/val_map.txt mlperf_conf_path : /home/cmuser/CM/repos/local/cache/5860c00d55d14786/inference/mlperf.conf multi_stream_expected_latency_ns : 0 @@ -26,7 +26,7 @@ tensor_path : build/preprocessed_data/open-images-v6-mlperf/validation/Retinanet test_mode : PerformanceOnly use_deque_limit : True use_graphs : True -user_conf_path : /home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/2d7ddffaece74235a135b34aa7023251.conf +user_conf_path : /home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/fdc1ee2ddd5740ac80a9fccb578452dc.conf system_id : RTX4090x2 config_name : RTX4090x2_retinanet_MultiStream workload_setting : WorkloadSetting(HarnessType.LWIS, AccuracyTarget.k_99, PowerSetting.MaxP) @@ -40,28 +40,28 @@ power_limit : None cpu_freq : None &&&& RUNNING Default_Harness # ./build/bin/harness_default [I] mlperf.conf path: /home/cmuser/CM/repos/local/cache/5860c00d55d14786/inference/mlperf.conf -[I] user.conf path: /home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/2d7ddffaece74235a135b34aa7023251.conf +[I] user.conf path: /home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/fdc1ee2ddd5740ac80a9fccb578452dc.conf Creating QSL. Finished Creating QSL. Setting up SUT. -[I] [TRT] Loaded engine size: 72 MiB -[I] [TRT] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +6, GPU +10, now: CPU 125, GPU 881 (MiB) -[I] [TRT] [MemUsageChange] Init cuDNN: CPU +2, GPU +10, now: CPU 127, GPU 891 (MiB) +[I] [TRT] Loaded engine size: 73 MiB +[I] [TRT] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +6, GPU +10, now: CPU 126, GPU 881 (MiB) +[I] [TRT] [MemUsageChange] Init cuDNN: CPU +2, GPU +10, now: CPU 128, GPU 891 (MiB) [I] [TRT] [MemUsageChange] TensorRT-managed allocation in engine deserialization: CPU +0, GPU +68, now: CPU 0, GPU 68 (MiB) [I] Device:0.GPU: [0] ./build/engines/RTX4090x2/retinanet/MultiStream/retinanet-MultiStream-gpu-b2-int8.lwis_k_99_MaxP.plan has been successfully loaded. -[I] [TRT] Loaded engine size: 72 MiB +[I] [TRT] Loaded engine size: 73 MiB [W] [TRT] Using an engine plan file across different models of devices is not recommended and is likely to affect performance or even cause errors. -[I] [TRT] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +6, GPU +10, now: CPU 159, GPU 624 (MiB) -[I] [TRT] [MemUsageChange] Init cuDNN: CPU +1, GPU +10, now: CPU 160, GPU 634 (MiB) +[I] [TRT] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +6, GPU +10, now: CPU 161, GPU 625 (MiB) +[I] [TRT] [MemUsageChange] Init cuDNN: CPU +1, GPU +10, now: CPU 162, GPU 635 (MiB) [I] [TRT] [MemUsageChange] TensorRT-managed allocation in engine deserialization: CPU +0, GPU +69, now: CPU 0, GPU 137 (MiB) [I] Device:1.GPU: [0] ./build/engines/RTX4090x2/retinanet/MultiStream/retinanet-MultiStream-gpu-b2-int8.lwis_k_99_MaxP.plan has been successfully loaded. [E] [TRT] 3: [runtime.cpp::~Runtime::401] Error Code 3: API Usage Error (Parameter check failed at: runtime/rt/runtime.cpp::~Runtime::401, condition: mEngineCounter.use_count() == 1 Destroying a runtime before destroying deserialized engines created by the runtime leads to undefined behavior.) -[I] [TRT] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +0, GPU +8, now: CPU 88, GPU 893 (MiB) -[I] [TRT] [MemUsageChange] Init cuDNN: CPU +0, GPU +8, now: CPU 88, GPU 901 (MiB) +[I] [TRT] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +0, GPU +8, now: CPU 89, GPU 893 (MiB) +[I] [TRT] [MemUsageChange] Init cuDNN: CPU +1, GPU +8, now: CPU 90, GPU 901 (MiB) [I] [TRT] [MemUsageChange] TensorRT-managed allocation in IExecutionContext creation: CPU +1, GPU +1528, now: CPU 1, GPU 1665 (MiB) -[I] [TRT] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +0, GPU +8, now: CPU 89, GPU 636 (MiB) -[I] [TRT] [MemUsageChange] Init cuDNN: CPU +0, GPU +8, now: CPU 89, GPU 644 (MiB) -[I] [TRT] [MemUsageChange] TensorRT-managed allocation in IExecutionContext creation: CPU +0, GPU +1528, now: CPU 1, GPU 3193 (MiB) +[I] [TRT] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +0, GPU +8, now: CPU 90, GPU 637 (MiB) +[I] [TRT] [MemUsageChange] Init cuDNN: CPU +0, GPU +8, now: CPU 90, GPU 645 (MiB) +[I] [TRT] [MemUsageChange] TensorRT-managed allocation in IExecutionContext creation: CPU +0, GPU +1527, now: CPU 1, GPU 3192 (MiB) [I] Start creating CUDA graphs [I] Capture 2 CUDA graphs [I] Capture 2 CUDA graphs @@ -69,7 +69,7 @@ Setting up SUT. [I] Creating batcher thread: 0 EnableBatcherThreadPerDevice: false Finished setting up SUT. Starting warmup. Running for a minimum of 5 seconds. -Finished warmup. Ran for 5.14308s. +Finished warmup. Ran for 5.14447s. Starting running actual test. ================================================ MLPerf Results Summary @@ -77,29 +77,29 @@ MLPerf Results Summary SUT name : LWIS_Server Scenario : MultiStream Mode : PerformanceOnly -99th percentile latency (ns) : 5651849 +99th percentile latency (ns) : 5619631 Result is : VALID Min duration satisfied : Yes Min queries satisfied : Yes Early stopping satisfied: Yes Early Stopping Result: - * Processed at least 662 queries (111606). - * Would discard 1037 highest latency queries. - * Early stopping 99th percentile estimate: 5654438 + * Processed at least 662 queries (111862). + * Would discard 1040 highest latency queries. + * Early stopping 99th percentile estimate: 5623507 ================================================ Additional Stats ================================================ Per-query latency: -Min latency (ns) : 5214573 -Max latency (ns) : 8069045 -Mean latency (ns) : 5357942 -50.00 percentile latency (ns) : 5336429 -90.00 percentile latency (ns) : 5431391 -95.00 percentile latency (ns) : 5523050 -97.00 percentile latency (ns) : 5593377 -99.00 percentile latency (ns) : 5651849 -99.90 percentile latency (ns) : 5807528 +Min latency (ns) : 5202031 +Max latency (ns) : 8045809 +Mean latency (ns) : 5349062 +50.00 percentile latency (ns) : 5331934 +90.00 percentile latency (ns) : 5416248 +95.00 percentile latency (ns) : 5460941 +97.00 percentile latency (ns) : 5521612 +99.00 percentile latency (ns) : 5619631 +99.90 percentile latency (ns) : 5768951 ================================================ Test Parameters Used @@ -129,17 +129,17 @@ No warnings encountered during test. No errors encountered during test. Finished running actual test. Device Device:0.GPU processed: - 223211 batches of size 2 + 223722 batches of size 2 Memcpy Calls: 0 PerSampleCudaMemcpy Calls: 0 - BatchedCudaMemcpy Calls: 223211 + BatchedCudaMemcpy Calls: 223722 Device Device:1.GPU processed: - 223213 batches of size 2 + 223726 batches of size 2 Memcpy Calls: 0 PerSampleCudaMemcpy Calls: 0 - BatchedCudaMemcpy Calls: 223213 + BatchedCudaMemcpy Calls: 223726 &&&& PASSED Default_Harness # ./build/bin/harness_default -[2024-12-23 02:36:20,734 run_harness.py:166 INFO] Result: result_99.00_percentile_per_query_latency_ns: 5651849, Result is VALID +[2024-12-25 01:40:33,416 run_harness.py:166 INFO] Result: result_99.00_percentile_per_query_latency_ns: 5619631, Result is VALID ======================== Result summaries: ======================== diff --git a/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/multistream/system_info.txt b/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/multistream/system_info.txt index 7bb0745b..41a8d4a6 100644 --- a/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/multistream/system_info.txt +++ b/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/multistream/system_info.txt @@ -2,10 +2,10 @@ Platform Details ------------------------------------------------------------ 1. uname -a -Linux e891b1c381b6 6.8.0-49-generic #49-Ubuntu SMP PREEMPT_DYNAMIC Mon Nov 4 02:06:24 UTC 2024 x86_64 x86_64 x86_64 GNU/Linux +Linux f77641321894 6.8.0-49-generic #49-Ubuntu SMP PREEMPT_DYNAMIC Mon Nov 4 02:06:24 UTC 2024 x86_64 x86_64 x86_64 GNU/Linux ------------------------------------------------------------ 2. w - 02:36:22 up 12 days, 20:54, 0 users, load average: 1.08, 1.12, 1.05 + 01:40:35 up 14 days, 19:58, 0 users, load average: 0.96, 1.04, 1.07 USER TTY FROM LOGIN@ IDLE JCPU PCPU WHAT ------------------------------------------------------------ 3. Username @@ -40,7 +40,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 4300.000 +cpu MHz : 1399.020 cache size : 46080 KB physical id : 0 siblings : 48 @@ -68,7 +68,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 2422.131 +cpu MHz : 800.000 cache size : 46080 KB physical id : 0 siblings : 48 @@ -96,7 +96,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 925.888 +cpu MHz : 800.000 cache size : 46080 KB physical id : 0 siblings : 48 @@ -124,7 +124,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 783.003 +cpu MHz : 800.000 cache size : 46080 KB physical id : 0 siblings : 48 @@ -404,7 +404,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 800.000 +cpu MHz : 4150.900 cache size : 46080 KB physical id : 0 siblings : 48 @@ -460,7 +460,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 972.712 +cpu MHz : 900.000 cache size : 46080 KB physical id : 0 siblings : 48 @@ -488,7 +488,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 3388.395 +cpu MHz : 1102.528 cache size : 46080 KB physical id : 0 siblings : 48 @@ -600,7 +600,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 3066.494 +cpu MHz : 800.000 cache size : 46080 KB physical id : 0 siblings : 48 @@ -656,7 +656,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 4300.000 +cpu MHz : 2700.000 cache size : 46080 KB physical id : 0 siblings : 48 @@ -684,7 +684,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 800.000 +cpu MHz : 4075.303 cache size : 46080 KB physical id : 0 siblings : 48 @@ -740,7 +740,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 800.000 +cpu MHz : 828.934 cache size : 46080 KB physical id : 0 siblings : 48 @@ -768,7 +768,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 851.312 +cpu MHz : 800.000 cache size : 46080 KB physical id : 0 siblings : 48 @@ -852,7 +852,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 800.095 +cpu MHz : 800.298 cache size : 46080 KB physical id : 0 siblings : 48 @@ -1076,7 +1076,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 1100.000 +cpu MHz : 800.000 cache size : 46080 KB physical id : 0 siblings : 48 @@ -1244,7 +1244,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 800.000 +cpu MHz : 1200.000 cache size : 46080 KB physical id : 0 siblings : 48 @@ -1272,7 +1272,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 800.000 +cpu MHz : 3999.556 cache size : 46080 KB physical id : 0 siblings : 48 @@ -1356,7 +1356,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 800.497 +cpu MHz : 800.000 cache size : 46080 KB physical id : 0 siblings : 48 @@ -1394,7 +1394,7 @@ CPU family: 6 Model: 143 Model name: Intel(R) Xeon(R) w7-2495X Stepping: 8 -CPU MHz: 4014.427 +CPU MHz: 4319.196 CPU max MHz: 4800.0000 CPU min MHz: 800.0000 BogoMIPS: 4992.00 @@ -1424,49 +1424,49 @@ Flags: fpu vme de pse tsc msr pae mce cx8 apic se available: 1 nodes (0) node 0 cpus: 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 node 0 size: 192709 MB -node 0 free: 18073 MB +node 0 free: 18344 MB node distances: node 0 0: 10 ------------------------------------------------------------ 9. /proc/meminfo MemTotal: 197334532 kB -MemFree: 18507548 kB -MemAvailable: 193229408 kB -Buffers: 453368 kB -Cached: 172424280 kB -SwapCached: 46224 kB -Active: 2803032 kB -Inactive: 170498804 kB -Active(anon): 371888 kB -Inactive(anon): 91752 kB -Active(file): 2431144 kB -Inactive(file): 170407052 kB +MemFree: 18784616 kB +MemAvailable: 193049204 kB +Buffers: 660160 kB +Cached: 169937564 kB +SwapCached: 37424 kB +Active: 4805056 kB +Inactive: 166242684 kB +Active(anon): 469712 kB +Inactive(anon): 18528 kB +Active(file): 4335344 kB +Inactive(file): 166224156 kB Unevictable: 3088 kB Mlocked: 0 kB SwapTotal: 8388604 kB -SwapFree: 7975300 kB +SwapFree: 7980272 kB Zswap: 0 kB Zswapped: 0 kB -Dirty: 324 kB +Dirty: 232 kB Writeback: 0 kB -AnonPages: 416360 kB -Mapped: 342048 kB -Shmem: 39452 kB -KReclaimable: 3655960 kB -Slab: 4655280 kB -SReclaimable: 3655960 kB -SUnreclaim: 999320 kB -KernelStack: 18016 kB -PageTables: 20964 kB +AnonPages: 446716 kB +Mapped: 337936 kB +Shmem: 38224 kB +KReclaimable: 5477384 kB +Slab: 6629980 kB +SReclaimable: 5477384 kB +SUnreclaim: 1152596 kB +KernelStack: 18304 kB +PageTables: 21524 kB SecPageTables: 0 kB NFS_Unstable: 0 kB Bounce: 0 kB WritebackTmp: 0 kB CommitLimit: 107055868 kB -Committed_AS: 5388516 kB +Committed_AS: 5496848 kB VmallocTotal: 13743895347199 kB -VmallocUsed: 156336 kB +VmallocUsed: 156616 kB VmallocChunk: 0 kB Percpu: 129600 kB HardwareCorrupted: 0 kB @@ -1482,8 +1482,8 @@ HugePages_Rsvd: 0 HugePages_Surp: 0 Hugepagesize: 2048 kB Hugetlb: 0 kB -DirectMap4k: 45491812 kB -DirectMap2M: 152168448 kB +DirectMap4k: 49012324 kB +DirectMap2M: 148647936 kB DirectMap1G: 5242880 kB ------------------------------------------------------------ 10. who -r @@ -1738,16 +1738,16 @@ dev.tty.ldisc_autoload = 1 dev.tty.legacy_tiocsti = 0 fs.aio-max-nr = 65536 fs.aio-nr = 0 -fs.dentry-state = 1399868 1286112 45 0 681183 0 +fs.dentry-state = 1882596 1735623 45 0 963594 0 fs.dir-notify-enable = 1 fs.epoll.max_user_watches = 43912503 fs.fanotify.max_queued_events = 16384 fs.fanotify.max_user_groups = 128 fs.fanotify.max_user_marks = 1048576 fs.file-max = 9223372036854775807 -fs.file-nr = 6080 0 9223372036854775807 -fs.inode-nr = 786206 176959 -fs.inode-state = 786206 176959 0 0 0 0 0 +fs.file-nr = 5888 0 9223372036854775807 +fs.inode-nr = 1245957 460543 +fs.inode-state = 1245957 460543 0 0 0 0 0 fs.inotify.max_queued_events = 16384 fs.inotify.max_user_instances = 128 fs.inotify.max_user_watches = 65536 @@ -1775,7 +1775,7 @@ fs.quota.drops = 0 fs.quota.free_dquots = 0 fs.quota.lookups = 0 fs.quota.reads = 0 -fs.quota.syncs = 1460 +fs.quota.syncs = 1742 fs.quota.writes = 0 fs.suid_dumpable = 2 fs.verity.require_signatures = 0 @@ -1802,7 +1802,7 @@ kernel.ftrace_dump_on_oops = 0 kernel.ftrace_enabled = 1 kernel.hardlockup_all_cpu_backtrace = 0 kernel.hardlockup_panic = 0 -kernel.hostname = e891b1c381b6 +kernel.hostname = f77641321894 kernel.hotplug = kernel.hung_task_all_cpu_backtrace = 0 kernel.hung_task_check_count = 4194304 @@ -1834,7 +1834,7 @@ kernel.msgmnb = 16384 kernel.msgmni = 32000 kernel.ngroups_max = 65536 kernel.nmi_watchdog = 1 -kernel.ns_last_pid = 25849 +kernel.ns_last_pid = 25853 kernel.numa_balancing = 0 kernel.numa_balancing_promote_rate_limit_MBps = 65536 kernel.oops_all_cpu_backtrace = 0 @@ -1865,13 +1865,13 @@ kernel.printk_devkmsg = on kernel.printk_ratelimit = 5 kernel.printk_ratelimit_burst = 10 kernel.pty.max = 4096 -kernel.pty.nr = 8 +kernel.pty.nr = 9 kernel.pty.reserve = 1024 kernel.random.boot_id = 29685405-01e1-41c8-8cf0-dcaddcc1862c kernel.random.entropy_avail = 256 kernel.random.poolsize = 256 kernel.random.urandom_min_reseed_secs = 60 -kernel.random.uuid = c35d2cd6-72ad-46a4-90e8-4b40c5ceb10f +kernel.random.uuid = 781380fa-333f-42e8-9b89-4208eada25cc kernel.random.write_wakeup_threshold = 256 kernel.randomize_va_space = 2 kernel.real-root-dev = 0 diff --git a/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/multistream/user.conf b/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/multistream/user.conf index b19ace0b..834230ab 100644 --- a/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/multistream/user.conf +++ b/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/multistream/user.conf @@ -1,3 +1,3 @@ -retinanet.MultiStream.target_latency = 2.1431768000000004 +retinanet.MultiStream.target_latency = 2.1396248 retinanet.MultiStream.max_duration = 660000 retinanet.MultiStream.min_query_count = 662 diff --git a/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/offline/README.md b/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/offline/README.md index 1651e788..07a732b7 100644 --- a/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/offline/README.md +++ b/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/offline/README.md @@ -19,7 +19,7 @@ pip install -U cmind cm rm cache -f -cm pull repo mlcommons@mlperf-automations --checkout=225220c7d9bb7e66e5b9a1e1ebfc3e0180fbd094 +cm pull repo mlcommons@mlperf-automations --checkout=a90475d2de72bf0622cebe8d5ca8eb8c9d872fbd cm run script \ --tags=app,mlperf,inference,generic,_nvidia,_retinanet,_tensorrt,_cuda,_valid,_r4.1-dev_default,_offline \ @@ -71,7 +71,7 @@ cm run script \ --env.CM_DOCKER_REUSE_EXISTING_CONTAINER=yes \ --env.CM_DOCKER_DETACHED_MODE=yes \ --env.CM_MLPERF_INFERENCE_RESULTS_DIR_=/home/arjun/gh_action_results/valid_results \ - --env.CM_DOCKER_CONTAINER_ID=e891b1c381b6 \ + --env.CM_DOCKER_CONTAINER_ID=f77641321894 \ --env.CM_MLPERF_LOADGEN_COMPLIANCE_TEST=TEST01 \ --add_deps_recursive.compiler.tags=gcc \ --add_deps_recursive.coco2014-original.tags=_full \ @@ -129,7 +129,7 @@ Platform: RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config Model Precision: int8 ### Accuracy Results -`mAP`: `37.332`, Required accuracy for closed division `>= 37.1745` +`mAP`: `37.343`, Required accuracy for closed division `>= 37.1745` ### Performance Results -`Samples per second`: `1735.67` +`Samples per second`: `1733.25` diff --git a/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/offline/accuracy_console.out b/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/offline/accuracy_console.out index 1a7a82c0..4bf2f2f2 100644 --- a/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/offline/accuracy_console.out +++ b/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/offline/accuracy_console.out @@ -1,8 +1,8 @@ -[2024-12-23 02:04:30,385 main.py:229 INFO] Detected system ID: KnownSystem.RTX4090x2 -[2024-12-23 02:04:30,511 harness.py:249 INFO] The harness will load 2 plugins: ['build/plugins/NMSOptPlugin/libnmsoptplugin.so', 'build/plugins/retinanetConcatPlugin/libretinanetconcatplugin.so'] -[2024-12-23 02:04:30,511 generate_conf_files.py:107 INFO] Generated measurements/ entries for RTX4090x2_TRT/retinanet/Offline -[2024-12-23 02:04:30,512 __init__.py:46 INFO] Running command: ./build/bin/harness_default --plugins="build/plugins/NMSOptPlugin/libnmsoptplugin.so,build/plugins/retinanetConcatPlugin/libretinanetconcatplugin.so" --logfile_outdir="/cm-mount/home/arjun/gh_action_results/valid_results/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/offline/accuracy" --logfile_prefix="mlperf_log_" --performance_sample_count=64 --test_mode="AccuracyOnly" --gpu_copy_streams=2 --gpu_inference_streams=2 --use_deque_limit=true --gpu_batch_size=2 --map_path="data_maps/open-images-v6-mlperf/val_map.txt" --mlperf_conf_path="/home/cmuser/CM/repos/local/cache/5860c00d55d14786/inference/mlperf.conf" --tensor_path="build/preprocessed_data/open-images-v6-mlperf/validation/Retinanet/int8_linear" --use_graphs=false --user_conf_path="/home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/4caf11bced4e4a3d841600c99d73f2be.conf" --gpu_engines="./build/engines/RTX4090x2/retinanet/Offline/retinanet-Offline-gpu-b2-int8.lwis_k_99_MaxP.plan" --max_dlas=0 --scenario Offline --model retinanet --response_postprocess openimageeffnms -[2024-12-23 02:04:30,512 __init__.py:53 INFO] Overriding Environment +[2024-12-25 01:08:44,850 main.py:229 INFO] Detected system ID: KnownSystem.RTX4090x2 +[2024-12-25 01:08:44,982 harness.py:249 INFO] The harness will load 2 plugins: ['build/plugins/NMSOptPlugin/libnmsoptplugin.so', 'build/plugins/retinanetConcatPlugin/libretinanetconcatplugin.so'] +[2024-12-25 01:08:44,983 generate_conf_files.py:107 INFO] Generated measurements/ entries for RTX4090x2_TRT/retinanet/Offline +[2024-12-25 01:08:44,983 __init__.py:46 INFO] Running command: ./build/bin/harness_default --plugins="build/plugins/NMSOptPlugin/libnmsoptplugin.so,build/plugins/retinanetConcatPlugin/libretinanetconcatplugin.so" --logfile_outdir="/cm-mount/home/arjun/gh_action_results/valid_results/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/offline/accuracy" --logfile_prefix="mlperf_log_" --performance_sample_count=64 --test_mode="AccuracyOnly" --gpu_copy_streams=2 --gpu_inference_streams=2 --use_deque_limit=true --gpu_batch_size=2 --map_path="data_maps/open-images-v6-mlperf/val_map.txt" --mlperf_conf_path="/home/cmuser/CM/repos/local/cache/5860c00d55d14786/inference/mlperf.conf" --tensor_path="build/preprocessed_data/open-images-v6-mlperf/validation/Retinanet/int8_linear" --use_graphs=false --user_conf_path="/home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/5c1b2782c9314773bc69a31bd0a37246.conf" --gpu_engines="./build/engines/RTX4090x2/retinanet/Offline/retinanet-Offline-gpu-b2-int8.lwis_k_99_MaxP.plan" --max_dlas=0 --scenario Offline --model retinanet --response_postprocess openimageeffnms +[2024-12-25 01:08:44,983 __init__.py:53 INFO] Overriding Environment benchmark : Benchmark.Retinanet buffer_manager_thread_count : 0 data_dir : /home/cmuser/CM/repos/local/cache/4db00c74da1e44c8/data @@ -11,7 +11,7 @@ gpu_copy_streams : 2 gpu_inference_streams : 2 input_dtype : int8 input_format : linear -log_dir : /home/cmuser/CM/repos/local/cache/94a57f78972843c6/repo/closed/NVIDIA/build/logs/2024.12.23-02.04.28 +log_dir : /home/cmuser/CM/repos/local/cache/94a57f78972843c6/repo/closed/NVIDIA/build/logs/2024.12.25-01.08.43 map_path : data_maps/open-images-v6-mlperf/val_map.txt mlperf_conf_path : /home/cmuser/CM/repos/local/cache/5860c00d55d14786/inference/mlperf.conf offline_expected_qps : 0.0 @@ -23,7 +23,7 @@ tensor_path : build/preprocessed_data/open-images-v6-mlperf/validation/Retinanet test_mode : AccuracyOnly use_deque_limit : True use_graphs : False -user_conf_path : /home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/4caf11bced4e4a3d841600c99d73f2be.conf +user_conf_path : /home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/5c1b2782c9314773bc69a31bd0a37246.conf system_id : RTX4090x2 config_name : RTX4090x2_retinanet_Offline workload_setting : WorkloadSetting(HarnessType.LWIS, AccuracyTarget.k_99, PowerSetting.MaxP) @@ -37,13 +37,13 @@ power_limit : None cpu_freq : None &&&& RUNNING Default_Harness # ./build/bin/harness_default [I] mlperf.conf path: /home/cmuser/CM/repos/local/cache/5860c00d55d14786/inference/mlperf.conf -[I] user.conf path: /home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/4caf11bced4e4a3d841600c99d73f2be.conf +[I] user.conf path: /home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/5c1b2782c9314773bc69a31bd0a37246.conf Creating QSL. Finished Creating QSL. Setting up SUT. [I] [TRT] Loaded engine size: 73 MiB -[I] [TRT] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +7, GPU +10, now: CPU 128, GPU 883 (MiB) -[I] [TRT] [MemUsageChange] Init cuDNN: CPU +1, GPU +10, now: CPU 129, GPU 893 (MiB) +[I] [TRT] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +6, GPU +10, now: CPU 127, GPU 883 (MiB) +[I] [TRT] [MemUsageChange] Init cuDNN: CPU +2, GPU +10, now: CPU 129, GPU 893 (MiB) [I] [TRT] [MemUsageChange] TensorRT-managed allocation in engine deserialization: CPU +0, GPU +68, now: CPU 0, GPU 68 (MiB) [I] Device:0.GPU: [0] ./build/engines/RTX4090x2/retinanet/Offline/retinanet-Offline-gpu-b2-int8.lwis_k_99_MaxP.plan has been successfully loaded. [I] [TRT] Loaded engine size: 73 MiB @@ -63,14 +63,14 @@ Setting up SUT. [I] [TRT] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +1, GPU +8, now: CPU 95, GPU 648 (MiB) [I] [TRT] [MemUsageChange] Init cuDNN: CPU +0, GPU +8, now: CPU 95, GPU 656 (MiB) [I] [TRT] [MemUsageChange] TensorRT-managed allocation in IExecutionContext creation: CPU +0, GPU +1528, now: CPU 2, GPU 4720 (MiB) -[I] [TRT] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +0, GPU +8, now: CPU 95, GPU 2192 (MiB) -[I] [TRT] [MemUsageChange] Init cuDNN: CPU +1, GPU +12, now: CPU 96, GPU 2204 (MiB) +[I] [TRT] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +1, GPU +8, now: CPU 96, GPU 2192 (MiB) +[I] [TRT] [MemUsageChange] Init cuDNN: CPU +0, GPU +12, now: CPU 96, GPU 2204 (MiB) [I] [TRT] Could not set default profile 0 for execution context. Profile index must be set explicitly. [I] [TRT] [MemUsageChange] TensorRT-managed allocation in IExecutionContext creation: CPU +1, GPU +1528, now: CPU 3, GPU 6248 (MiB) [I] Creating batcher thread: 0 EnableBatcherThreadPerDevice: false Finished setting up SUT. Starting warmup. Running for a minimum of 5 seconds. -Finished warmup. Ran for 5.03745s. +Finished warmup. Ran for 5.03403s. Starting running actual test. No warnings encountered during test. @@ -89,34 +89,34 @@ Device Device:1.GPU processed: PerSampleCudaMemcpy Calls: 0 BatchedCudaMemcpy Calls: 6195 &&&& PASSED Default_Harness # ./build/bin/harness_default -[2024-12-23 02:05:07,109 run_harness.py:166 INFO] Result: Accuracy run detected. -[2024-12-23 02:05:07,110 __init__.py:46 INFO] Running command: python3 /home/cmuser/CM/repos/local/cache/94a57f78972843c6/repo/closed/NVIDIA/build/inference/vision/classification_and_detection/tools/accuracy-openimages.py --mlperf-accuracy-file /cm-mount/home/arjun/gh_action_results/valid_results/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/offline/accuracy/mlperf_log_accuracy.json --openimages-dir /home/cmuser/CM/repos/local/cache/4db00c74da1e44c8/preprocessed_data/open-images-v6-mlperf --output-file build/retinanet-results.json +[2024-12-25 01:09:19,273 run_harness.py:166 INFO] Result: Accuracy run detected. +[2024-12-25 01:09:19,273 __init__.py:46 INFO] Running command: python3 /home/cmuser/CM/repos/local/cache/94a57f78972843c6/repo/closed/NVIDIA/build/inference/vision/classification_and_detection/tools/accuracy-openimages.py --mlperf-accuracy-file /cm-mount/home/arjun/gh_action_results/valid_results/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/offline/accuracy/mlperf_log_accuracy.json --openimages-dir /home/cmuser/CM/repos/local/cache/4db00c74da1e44c8/preprocessed_data/open-images-v6-mlperf --output-file build/retinanet-results.json loading annotations into memory... -Done (t=0.50s) +Done (t=0.45s) creating index... index created! Loading and preparing results... -DONE (t=17.80s) +DONE (t=17.75s) creating index... index created! Running per image evaluation... Evaluate annotation type *bbox* -DONE (t=133.87s). +DONE (t=135.38s). Accumulating evaluation results... -DONE (t=32.08s). +DONE (t=32.42s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.373 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.522 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.404 - Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.022 + Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.023 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.125 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.413 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.419 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.599 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.628 - Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.081 - Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.343 - Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.678 -mAP=37.332% + Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.083 + Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.344 + Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.677 +mAP=37.343% ======================== Result summaries: ======================== diff --git a/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/offline/cm-deps.mmd b/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/offline/cm-deps.mmd index 5f5f5dc7..e6e3173e 100644 --- a/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/offline/cm-deps.mmd +++ b/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/offline/cm-deps.mmd @@ -14,19 +14,19 @@ graph TD get-generic-python-lib,94b62a682bc44791_(_package.numpy_) --> get,python3 get-cuda-devices,7a3ede4d3558427a_(_with-pycuda_) --> get,generic-python-lib,_package.numpy app-mlperf-inference,d775cac873ee4231_(_nvidia,_retinanet,_tensorrt,_cuda,_valid,_r4.1-dev_default,_offline_) --> get,cuda-devices,_with-pycuda - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_cuda,_retinanet,_offline,_rtx_4090_) --> detect,os + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_offline,_cuda,_tensorrt,_retinanet,_rtx_4090_) --> detect,os detect-cpu,586c8a43320142f7 --> detect,os - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_cuda,_retinanet,_offline,_rtx_4090_) --> detect,cpu - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_cuda,_retinanet,_offline,_rtx_4090_) --> get,sys-utils-cm - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_cuda,_retinanet,_offline,_rtx_4090_) --> get,mlperf,inference,nvidia,scratch,space + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_offline,_cuda,_tensorrt,_retinanet,_rtx_4090_) --> detect,cpu + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_offline,_cuda,_tensorrt,_retinanet,_rtx_4090_) --> get,sys-utils-cm + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_offline,_cuda,_tensorrt,_retinanet,_rtx_4090_) --> get,mlperf,inference,nvidia,scratch,space get-generic-python-lib,94b62a682bc44791_(_mlperf_logging_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_cuda,_retinanet,_offline,_rtx_4090_) --> get,generic-python-lib,_mlperf_logging - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_cuda,_retinanet,_offline,_rtx_4090_) --> get,dataset,original,openimages,_validation,_full,_custom-annotations - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_cuda,_retinanet,_offline,_rtx_4090_) --> get,dataset,original,openimages,_calibration - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_cuda,_retinanet,_offline,_rtx_4090_) --> get,mlcommons,inference,src - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_cuda,_retinanet,_offline,_rtx_4090_) --> get,nvidia,mlperf,inference,common-code,_mlcommons + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_offline,_cuda,_tensorrt,_retinanet,_rtx_4090_) --> get,generic-python-lib,_mlperf_logging + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_offline,_cuda,_tensorrt,_retinanet,_rtx_4090_) --> get,dataset,original,openimages,_validation,_full,_custom-annotations + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_offline,_cuda,_tensorrt,_retinanet,_rtx_4090_) --> get,dataset,original,openimages,_calibration + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_offline,_cuda,_tensorrt,_retinanet,_rtx_4090_) --> get,mlcommons,inference,src + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_offline,_cuda,_tensorrt,_retinanet,_rtx_4090_) --> get,nvidia,mlperf,inference,common-code,_mlcommons pull-git-repo,c23132ed65c4421d --> detect,os - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_cuda,_retinanet,_offline,_rtx_4090_) --> pull,git,repo + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_offline,_cuda,_tensorrt,_retinanet,_rtx_4090_) --> pull,git,repo generate-mlperf-inference-user-conf,3af4475745964b93 --> detect,os detect-cpu,586c8a43320142f7 --> detect,os generate-mlperf-inference-user-conf,3af4475745964b93 --> detect,cpu @@ -34,67 +34,67 @@ graph TD generate-mlperf-inference-user-conf,3af4475745964b93 --> get,mlcommons,inference,src get-mlperf-inference-sut-configs,c2fbf72009e2445b --> get,cache,dir,_name.mlperf-inference-sut-configs generate-mlperf-inference-user-conf,3af4475745964b93 --> get,sut,configs - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_cuda,_retinanet,_offline,_rtx_4090_) --> generate,user-conf,mlperf,inference + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_offline,_cuda,_tensorrt,_retinanet,_rtx_4090_) --> generate,user-conf,mlperf,inference get-generic-python-lib,94b62a682bc44791_(_package.pycuda_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_cuda,_retinanet,_offline,_rtx_4090_) --> get,generic-python-lib,_package.pycuda - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_cuda,_retinanet,_offline,_rtx_4090_) --> get,nvidia,mitten - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_cuda,_retinanet,_offline,_rtx_4090_) --> get,cuda,_cudnn - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_cuda,_retinanet,_offline,_rtx_4090_) --> get,tensorrt - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_cuda,_retinanet,_offline,_rtx_4090_) --> build,nvidia,inference,server,_mlcommons - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_cuda,_retinanet,_offline,_batch_size.2,_v4.1-dev_) --> detect,os + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_offline,_cuda,_tensorrt,_retinanet,_rtx_4090_) --> get,generic-python-lib,_package.pycuda + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_offline,_cuda,_tensorrt,_retinanet,_rtx_4090_) --> get,nvidia,mitten + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_offline,_cuda,_tensorrt,_retinanet,_rtx_4090_) --> get,cuda,_cudnn + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_offline,_cuda,_tensorrt,_retinanet,_rtx_4090_) --> get,tensorrt + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_offline,_cuda,_tensorrt,_retinanet,_rtx_4090_) --> build,nvidia,inference,server,_mlcommons + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_offline,_cuda,_tensorrt,_retinanet,_batch_size.2,_v4.1-dev_) --> detect,os detect-cpu,586c8a43320142f7 --> detect,os - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_cuda,_retinanet,_offline,_batch_size.2,_v4.1-dev_) --> detect,cpu - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_cuda,_retinanet,_offline,_batch_size.2,_v4.1-dev_) --> get,sys-utils-cm - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_cuda,_retinanet,_offline,_batch_size.2,_v4.1-dev_) --> get,mlperf,inference,nvidia,scratch,space,_version.4_0 + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_offline,_cuda,_tensorrt,_retinanet,_batch_size.2,_v4.1-dev_) --> detect,cpu + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_offline,_cuda,_tensorrt,_retinanet,_batch_size.2,_v4.1-dev_) --> get,sys-utils-cm + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_offline,_cuda,_tensorrt,_retinanet,_batch_size.2,_v4.1-dev_) --> get,mlperf,inference,nvidia,scratch,space,_version.4_0 get-generic-python-lib,94b62a682bc44791_(_mlperf_logging_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_cuda,_retinanet,_offline,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_mlperf_logging - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_cuda,_retinanet,_offline,_batch_size.2,_v4.1-dev_) --> get,dataset,original,openimages,_validation,_full,_custom-annotations - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_cuda,_retinanet,_offline,_batch_size.2,_v4.1-dev_) --> get,dataset,original,openimages,_calibration - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_cuda,_retinanet,_offline,_batch_size.2,_v4.1-dev_) --> get,mlcommons,inference,src - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_cuda,_retinanet,_offline,_batch_size.2,_v4.1-dev_) --> get,nvidia,mlperf,inference,common-code,_mlcommons + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_offline,_cuda,_tensorrt,_retinanet,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_mlperf_logging + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_offline,_cuda,_tensorrt,_retinanet,_batch_size.2,_v4.1-dev_) --> get,dataset,original,openimages,_validation,_full,_custom-annotations + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_offline,_cuda,_tensorrt,_retinanet,_batch_size.2,_v4.1-dev_) --> get,dataset,original,openimages,_calibration + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_offline,_cuda,_tensorrt,_retinanet,_batch_size.2,_v4.1-dev_) --> get,mlcommons,inference,src + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_offline,_cuda,_tensorrt,_retinanet,_batch_size.2,_v4.1-dev_) --> get,nvidia,mlperf,inference,common-code,_mlcommons pull-git-repo,c23132ed65c4421d --> detect,os - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_cuda,_retinanet,_offline,_batch_size.2,_v4.1-dev_) --> pull,git,repo + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_offline,_cuda,_tensorrt,_retinanet,_batch_size.2,_v4.1-dev_) --> pull,git,repo get-generic-python-lib,94b62a682bc44791_(_package.pycuda_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_cuda,_retinanet,_offline,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_package.pycuda - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_cuda,_retinanet,_offline,_batch_size.2,_v4.1-dev_) --> get,nvidia,mitten - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_cuda,_retinanet,_offline,_batch_size.2,_v4.1-dev_) --> get,cuda,_cudnn - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_cuda,_retinanet,_offline,_batch_size.2,_v4.1-dev_) --> get,tensorrt - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_cuda,_retinanet,_offline,_batch_size.2,_v4.1-dev_) --> build,nvidia,inference,server,_mlcommons - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_cuda,_retinanet,_offline,_batch_size.2,_v4.1-dev_) --> reproduce,mlperf,inference,nvidia,harness,_preprocess_data,_tensorrt,_cuda,_retinanet,_v4.1-dev - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_cuda,_retinanet,_offline,_batch_size.2,_v4.1-dev_) --> reproduce,mlperf,inference,nvidia,harness,_download_model,_tensorrt,_cuda,_retinanet,_v4.1-dev - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_cuda,_retinanet,_offline,_batch_size.2,_v4.1-dev_) --> reproduce,mlperf,inference,nvidia,harness,_calibrate,_tensorrt,_cuda,_retinanet,_v4.1-dev + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_offline,_cuda,_tensorrt,_retinanet,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_package.pycuda + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_offline,_cuda,_tensorrt,_retinanet,_batch_size.2,_v4.1-dev_) --> get,nvidia,mitten + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_offline,_cuda,_tensorrt,_retinanet,_batch_size.2,_v4.1-dev_) --> get,cuda,_cudnn + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_offline,_cuda,_tensorrt,_retinanet,_batch_size.2,_v4.1-dev_) --> get,tensorrt + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_offline,_cuda,_tensorrt,_retinanet,_batch_size.2,_v4.1-dev_) --> build,nvidia,inference,server,_mlcommons + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_offline,_cuda,_tensorrt,_retinanet,_batch_size.2,_v4.1-dev_) --> reproduce,mlperf,inference,nvidia,harness,_preprocess_data,_cuda,_tensorrt,_retinanet,_v4.1-dev + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_offline,_cuda,_tensorrt,_retinanet,_batch_size.2,_v4.1-dev_) --> reproduce,mlperf,inference,nvidia,harness,_download_model,_cuda,_tensorrt,_retinanet,_v4.1-dev + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_offline,_cuda,_tensorrt,_retinanet,_batch_size.2,_v4.1-dev_) --> reproduce,mlperf,inference,nvidia,harness,_calibrate,_cuda,_tensorrt,_retinanet,_v4.1-dev get-generic-python-lib,94b62a682bc44791_(_Pillow_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_cuda,_retinanet,_offline,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_Pillow + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_offline,_cuda,_tensorrt,_retinanet,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_Pillow get-generic-python-lib,94b62a682bc44791_(_opencv-python_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_cuda,_retinanet,_offline,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_opencv-python + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_offline,_cuda,_tensorrt,_retinanet,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_opencv-python get-generic-python-lib,94b62a682bc44791_(_numpy_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_cuda,_retinanet,_offline,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_numpy + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_offline,_cuda,_tensorrt,_retinanet,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_numpy get-generic-python-lib,94b62a682bc44791_(_pycocotools_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_cuda,_retinanet,_offline,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_pycocotools + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_offline,_cuda,_tensorrt,_retinanet,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_pycocotools get-generic-python-lib,94b62a682bc44791_(_onnx-graphsurgeon_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_cuda,_retinanet,_offline,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_onnx-graphsurgeon + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_offline,_cuda,_tensorrt,_retinanet,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_onnx-graphsurgeon get-generic-python-lib,94b62a682bc44791_(_package.onnx_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_cuda,_retinanet,_offline,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_package.onnx + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_offline,_cuda,_tensorrt,_retinanet,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_package.onnx get-generic-python-lib,94b62a682bc44791_(_package.sympy_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_cuda,_retinanet,_offline,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_package.sympy - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_cuda,_retinanet,_offline,_batch_size.2,_v4.1-dev_) --> save,mlperf,inference,state - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_cuda,_retinanet,_offline,_rtx_4090_) --> reproduce,mlperf,inference,nvidia,harness,_build_engine,_tensorrt,_cuda,_retinanet,_offline,_batch_size.2,_v4.1-dev - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_cuda,_retinanet,_offline,_rtx_4090_) --> reproduce,mlperf,inference,nvidia,harness,_preprocess_data,_tensorrt,_cuda,_retinanet,_v4.1-dev + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_offline,_cuda,_tensorrt,_retinanet,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_package.sympy + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_offline,_cuda,_tensorrt,_retinanet,_batch_size.2,_v4.1-dev_) --> save,mlperf,inference,state + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_offline,_cuda,_tensorrt,_retinanet,_rtx_4090_) --> reproduce,mlperf,inference,nvidia,harness,_build_engine,_offline,_cuda,_tensorrt,_retinanet,_batch_size.2,_v4.1-dev + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_offline,_cuda,_tensorrt,_retinanet,_rtx_4090_) --> reproduce,mlperf,inference,nvidia,harness,_preprocess_data,_cuda,_tensorrt,_retinanet,_v4.1-dev get-generic-python-lib,94b62a682bc44791_(_Pillow_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_cuda,_retinanet,_offline,_rtx_4090_) --> get,generic-python-lib,_Pillow + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_offline,_cuda,_tensorrt,_retinanet,_rtx_4090_) --> get,generic-python-lib,_Pillow get-generic-python-lib,94b62a682bc44791_(_opencv-python_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_cuda,_retinanet,_offline,_rtx_4090_) --> get,generic-python-lib,_opencv-python + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_offline,_cuda,_tensorrt,_retinanet,_rtx_4090_) --> get,generic-python-lib,_opencv-python get-generic-python-lib,94b62a682bc44791_(_numpy_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_cuda,_retinanet,_offline,_rtx_4090_) --> get,generic-python-lib,_numpy + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_offline,_cuda,_tensorrt,_retinanet,_rtx_4090_) --> get,generic-python-lib,_numpy get-generic-python-lib,94b62a682bc44791_(_pycocotools_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_cuda,_retinanet,_offline,_rtx_4090_) --> get,generic-python-lib,_pycocotools + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_offline,_cuda,_tensorrt,_retinanet,_rtx_4090_) --> get,generic-python-lib,_pycocotools get-generic-python-lib,94b62a682bc44791_(_onnx-graphsurgeon_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_cuda,_retinanet,_offline,_rtx_4090_) --> get,generic-python-lib,_onnx-graphsurgeon + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_offline,_cuda,_tensorrt,_retinanet,_rtx_4090_) --> get,generic-python-lib,_onnx-graphsurgeon get-generic-python-lib,94b62a682bc44791_(_package.onnx_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_cuda,_retinanet,_offline,_rtx_4090_) --> get,generic-python-lib,_package.onnx + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_offline,_cuda,_tensorrt,_retinanet,_rtx_4090_) --> get,generic-python-lib,_package.onnx get-generic-python-lib,94b62a682bc44791_(_package.sympy_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_cuda,_retinanet,_offline,_rtx_4090_) --> get,generic-python-lib,_package.sympy + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_offline,_cuda,_tensorrt,_retinanet,_rtx_4090_) --> get,generic-python-lib,_package.sympy detect-cpu,586c8a43320142f7 --> detect,os benchmark-program,19f369ef47084895 --> detect,cpu benchmark-program-mlperf,cfff0132a8aa4018 --> benchmark-program,program - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_cuda,_retinanet,_offline,_rtx_4090_) --> benchmark-mlperf \ No newline at end of file + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_offline,_cuda,_tensorrt,_retinanet,_rtx_4090_) --> benchmark-mlperf \ No newline at end of file diff --git a/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/offline/cm-deps.png b/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/offline/cm-deps.png index 698b2112..43686df5 100644 Binary files a/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/offline/cm-deps.png and b/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/offline/cm-deps.png differ diff --git a/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/offline/cm-version-info.json b/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/offline/cm-version-info.json index 9f4379c1..47a367cd 100644 --- a/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/offline/cm-version-info.json +++ b/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/offline/cm-version-info.json @@ -157,7 +157,7 @@ "script_tags": "detect-os,detect,os,info", "script_variations": "", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_cuda,_retinanet,_offline,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_offline,_cuda,_tensorrt,_retinanet,_rtx_4090 )" } }, { @@ -177,7 +177,7 @@ "script_tags": "detect,cpu,detect-cpu,info", "script_variations": "", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_cuda,_retinanet,_offline,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_offline,_cuda,_tensorrt,_retinanet,_rtx_4090 )" } }, { @@ -187,7 +187,7 @@ "script_tags": "get,sys-utils-cm", "script_variations": "", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_cuda,_retinanet,_offline,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_offline,_cuda,_tensorrt,_retinanet,_rtx_4090 )" } }, { @@ -197,7 +197,7 @@ "script_tags": "get,mlperf,inference,nvidia,scratch,space", "script_variations": "", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_cuda,_retinanet,_offline,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_offline,_cuda,_tensorrt,_retinanet,_rtx_4090 )" } }, { @@ -217,7 +217,7 @@ "script_tags": "get,install,generic,pip-package,generic-python-lib", "script_variations": "mlperf_logging", "version": "4.1.1", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_cuda,_retinanet,_offline,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_offline,_cuda,_tensorrt,_retinanet,_rtx_4090 )" } }, { @@ -227,7 +227,7 @@ "script_tags": "get,dataset,openimages,open-images,object-detection,original", "script_variations": "validation,full,custom-annotations", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_cuda,_retinanet,_offline,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_offline,_cuda,_tensorrt,_retinanet,_rtx_4090 )" } }, { @@ -237,7 +237,7 @@ "script_tags": "get,dataset,openimages,open-images,object-detection,original", "script_variations": "calibration", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_cuda,_retinanet,_offline,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_offline,_cuda,_tensorrt,_retinanet,_rtx_4090 )" } }, { @@ -247,7 +247,7 @@ "script_tags": "get,src,source,inference,inference-src,inference-source,mlperf,mlcommons", "script_variations": "", "version": "master-git-2fdb814e6a765d994872fb99ee38f8c43418d5b0", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_cuda,_retinanet,_offline,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_offline,_cuda,_tensorrt,_retinanet,_rtx_4090 )" } }, { @@ -257,7 +257,7 @@ "script_tags": "get,nvidia,mlperf,inference,common-code", "script_variations": "mlcommons", "version": "r4.0", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_cuda,_retinanet,_offline,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_offline,_cuda,_tensorrt,_retinanet,_rtx_4090 )" } }, { @@ -277,7 +277,7 @@ "script_tags": "pull,git,repo,repository", "script_variations": "", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_cuda,_retinanet,_offline,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_offline,_cuda,_tensorrt,_retinanet,_rtx_4090 )" } }, { @@ -357,7 +357,7 @@ "script_tags": "generate,mlperf,inference,user-conf,inference-user-conf", "script_variations": "", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_cuda,_retinanet,_offline,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_offline,_cuda,_tensorrt,_retinanet,_rtx_4090 )" } }, { @@ -377,7 +377,7 @@ "script_tags": "get,install,generic,pip-package,generic-python-lib", "script_variations": "package.pycuda", "version": "2022.2.2", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_cuda,_retinanet,_offline,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_offline,_cuda,_tensorrt,_retinanet,_rtx_4090 )" } }, { @@ -387,7 +387,7 @@ "script_tags": "get,nvidia,mitten,nvidia-mitten", "script_variations": "", "version": "master", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_cuda,_retinanet,_offline,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_offline,_cuda,_tensorrt,_retinanet,_rtx_4090 )" } }, { @@ -397,7 +397,7 @@ "script_tags": "get,cuda,cuda-compiler,cuda-lib,toolkit,lib,nvcc,get-nvcc,get-cuda,46d133d9ef92422d", "script_variations": "cudnn", "version": "12.2", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_cuda,_retinanet,_offline,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_offline,_cuda,_tensorrt,_retinanet,_rtx_4090 )" } }, { @@ -407,7 +407,7 @@ "script_tags": "get,tensorrt,nvidia", "script_variations": "", "version": "vdetected", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_cuda,_retinanet,_offline,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_offline,_cuda,_tensorrt,_retinanet,_rtx_4090 )" } }, { @@ -417,7 +417,7 @@ "script_tags": "build,mlcommons,mlperf,inference,inference-server,server,nvidia-harness,nvidia", "script_variations": "mlcommons", "version": "r4.0", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_cuda,_retinanet,_offline,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_offline,_cuda,_tensorrt,_retinanet,_rtx_4090 )" } }, { @@ -427,7 +427,7 @@ "script_tags": "detect-os,detect,os,info", "script_variations": "", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( build_engine,_tensorrt,_cuda,_retinanet,_offline,_batch_size.2,_v4.1-dev )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( build_engine,_offline,_cuda,_tensorrt,_retinanet,_batch_size.2,_v4.1-dev )" } }, { @@ -447,7 +447,7 @@ "script_tags": "detect,cpu,detect-cpu,info", "script_variations": "", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( build_engine,_tensorrt,_cuda,_retinanet,_offline,_batch_size.2,_v4.1-dev )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( build_engine,_offline,_cuda,_tensorrt,_retinanet,_batch_size.2,_v4.1-dev )" } }, { @@ -457,7 +457,7 @@ "script_tags": "get,sys-utils-cm", "script_variations": "", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( build_engine,_tensorrt,_cuda,_retinanet,_offline,_batch_size.2,_v4.1-dev )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( build_engine,_offline,_cuda,_tensorrt,_retinanet,_batch_size.2,_v4.1-dev )" } }, { @@ -467,7 +467,7 @@ "script_tags": "get,mlperf,inference,nvidia,scratch,space", "script_variations": "version.4_0", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( build_engine,_tensorrt,_cuda,_retinanet,_offline,_batch_size.2,_v4.1-dev )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( build_engine,_offline,_cuda,_tensorrt,_retinanet,_batch_size.2,_v4.1-dev )" } }, { @@ -487,7 +487,7 @@ "script_tags": "get,install,generic,pip-package,generic-python-lib", "script_variations": "mlperf_logging", "version": "4.1.1", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( build_engine,_tensorrt,_cuda,_retinanet,_offline,_batch_size.2,_v4.1-dev )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( build_engine,_offline,_cuda,_tensorrt,_retinanet,_batch_size.2,_v4.1-dev )" } }, { @@ -497,7 +497,7 @@ "script_tags": "get,dataset,openimages,open-images,object-detection,original", "script_variations": "validation,full,custom-annotations", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( build_engine,_tensorrt,_cuda,_retinanet,_offline,_batch_size.2,_v4.1-dev )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( build_engine,_offline,_cuda,_tensorrt,_retinanet,_batch_size.2,_v4.1-dev )" } }, { @@ -507,7 +507,7 @@ "script_tags": "get,dataset,openimages,open-images,object-detection,original", "script_variations": "calibration", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( build_engine,_tensorrt,_cuda,_retinanet,_offline,_batch_size.2,_v4.1-dev )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( build_engine,_offline,_cuda,_tensorrt,_retinanet,_batch_size.2,_v4.1-dev )" } }, { @@ -517,7 +517,7 @@ "script_tags": "get,src,source,inference,inference-src,inference-source,mlperf,mlcommons", "script_variations": "", "version": "master-git-2fdb814e6a765d994872fb99ee38f8c43418d5b0", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( build_engine,_tensorrt,_cuda,_retinanet,_offline,_batch_size.2,_v4.1-dev )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( build_engine,_offline,_cuda,_tensorrt,_retinanet,_batch_size.2,_v4.1-dev )" } }, { @@ -527,7 +527,7 @@ "script_tags": "get,nvidia,mlperf,inference,common-code", "script_variations": "mlcommons", "version": "r4.0", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( build_engine,_tensorrt,_cuda,_retinanet,_offline,_batch_size.2,_v4.1-dev )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( build_engine,_offline,_cuda,_tensorrt,_retinanet,_batch_size.2,_v4.1-dev )" } }, { @@ -547,7 +547,7 @@ "script_tags": "pull,git,repo,repository", "script_variations": "", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( build_engine,_tensorrt,_cuda,_retinanet,_offline,_batch_size.2,_v4.1-dev )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( build_engine,_offline,_cuda,_tensorrt,_retinanet,_batch_size.2,_v4.1-dev )" } }, { @@ -567,7 +567,7 @@ "script_tags": "get,install,generic,pip-package,generic-python-lib", "script_variations": "package.pycuda", "version": "2022.2.2", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( build_engine,_tensorrt,_cuda,_retinanet,_offline,_batch_size.2,_v4.1-dev )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( build_engine,_offline,_cuda,_tensorrt,_retinanet,_batch_size.2,_v4.1-dev )" } }, { @@ -577,7 +577,7 @@ "script_tags": "get,nvidia,mitten,nvidia-mitten", "script_variations": "", "version": "master", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( build_engine,_tensorrt,_cuda,_retinanet,_offline,_batch_size.2,_v4.1-dev )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( build_engine,_offline,_cuda,_tensorrt,_retinanet,_batch_size.2,_v4.1-dev )" } }, { @@ -587,7 +587,7 @@ "script_tags": "get,cuda,cuda-compiler,cuda-lib,toolkit,lib,nvcc,get-nvcc,get-cuda,46d133d9ef92422d", "script_variations": "cudnn", "version": "12.2", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( build_engine,_tensorrt,_cuda,_retinanet,_offline,_batch_size.2,_v4.1-dev )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( build_engine,_offline,_cuda,_tensorrt,_retinanet,_batch_size.2,_v4.1-dev )" } }, { @@ -597,7 +597,7 @@ "script_tags": "get,tensorrt,nvidia", 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build_engine,_tensorrt,_cuda,_retinanet,_offline,_batch_size.2,_v4.1-dev )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( build_engine,_offline,_cuda,_tensorrt,_retinanet,_batch_size.2,_v4.1-dev )" } }, { @@ -657,7 +657,7 @@ "script_tags": "get,install,generic,pip-package,generic-python-lib", "script_variations": "Pillow", "version": "10.4.0", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( build_engine,_tensorrt,_cuda,_retinanet,_offline,_batch_size.2,_v4.1-dev )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( build_engine,_offline,_cuda,_tensorrt,_retinanet,_batch_size.2,_v4.1-dev )" } }, { @@ -677,7 +677,7 @@ "script_tags": "get,install,generic,pip-package,generic-python-lib", "script_variations": "opencv-python", "version": "4.10.0.84", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( build_engine,_tensorrt,_cuda,_retinanet,_offline,_batch_size.2,_v4.1-dev )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( build_engine,_offline,_cuda,_tensorrt,_retinanet,_batch_size.2,_v4.1-dev )" } }, { @@ -697,7 +697,7 @@ "script_tags": "get,install,generic,pip-package,generic-python-lib", "script_variations": "numpy", "version": "1.23.5", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( build_engine,_tensorrt,_cuda,_retinanet,_offline,_batch_size.2,_v4.1-dev )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( build_engine,_offline,_cuda,_tensorrt,_retinanet,_batch_size.2,_v4.1-dev )" } }, { @@ -717,7 +717,7 @@ "script_tags": "get,install,generic,pip-package,generic-python-lib", "script_variations": "pycocotools", "version": "2.0.7", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( build_engine,_tensorrt,_cuda,_retinanet,_offline,_batch_size.2,_v4.1-dev )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( build_engine,_offline,_cuda,_tensorrt,_retinanet,_batch_size.2,_v4.1-dev )" } }, { @@ -737,7 +737,7 @@ "script_tags": 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"script_tags": "reproduce,mlcommons,mlperf,inference,harness,nvidia-harness,nvidia", - "script_variations": "build_engine,tensorrt,cuda,retinanet,offline,batch_size.2,v4.1-dev", + "script_variations": "build_engine,offline,cuda,tensorrt,retinanet,batch_size.2,v4.1-dev", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_cuda,_retinanet,_offline,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_offline,_cuda,_tensorrt,_retinanet,_rtx_4090 )" } }, { - "reproduce,mlperf,inference,nvidia,harness,_preprocess_data,_tensorrt,_cuda,_retinanet,_v4.1-dev": { + "reproduce,mlperf,inference,nvidia,harness,_preprocess_data,_cuda,_tensorrt,_retinanet,_v4.1-dev": { "script_uid": "bc3b17fb430f4732", "script_alias": "app-mlperf-inference-nvidia", "script_tags": "reproduce,mlcommons,mlperf,inference,harness,nvidia-harness,nvidia", - "script_variations": "preprocess_data,tensorrt,cuda,retinanet,v4.1-dev", + "script_variations": "preprocess_data,cuda,tensorrt,retinanet,v4.1-dev", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_cuda,_retinanet,_offline,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_offline,_cuda,_tensorrt,_retinanet,_rtx_4090 )" } }, { @@ -827,7 +827,7 @@ "script_tags": "get,install,generic,pip-package,generic-python-lib", "script_variations": "Pillow", "version": "10.4.0", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_cuda,_retinanet,_offline,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_offline,_cuda,_tensorrt,_retinanet,_rtx_4090 )" } }, { @@ -847,7 +847,7 @@ "script_tags": "get,install,generic,pip-package,generic-python-lib", "script_variations": "opencv-python", "version": "4.10.0.84", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_cuda,_retinanet,_offline,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_offline,_cuda,_tensorrt,_retinanet,_rtx_4090 )" } }, { @@ -867,7 +867,7 @@ "script_tags": "get,install,generic,pip-package,generic-python-lib", "script_variations": "numpy", "version": "1.23.5", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_cuda,_retinanet,_offline,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_offline,_cuda,_tensorrt,_retinanet,_rtx_4090 )" } }, { @@ -887,7 +887,7 @@ "script_tags": "get,install,generic,pip-package,generic-python-lib", "script_variations": "pycocotools", "version": "2.0.7", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_cuda,_retinanet,_offline,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_offline,_cuda,_tensorrt,_retinanet,_rtx_4090 )" } }, { @@ -907,7 +907,7 @@ "script_tags": "get,install,generic,pip-package,generic-python-lib", "script_variations": "onnx-graphsurgeon", "version": "0.3.27", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_cuda,_retinanet,_offline,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_offline,_cuda,_tensorrt,_retinanet,_rtx_4090 )" } }, { @@ -927,7 +927,7 @@ "script_tags": "get,install,generic,pip-package,generic-python-lib", "script_variations": "package.onnx", "version": "1.14.1", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_cuda,_retinanet,_offline,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_offline,_cuda,_tensorrt,_retinanet,_rtx_4090 )" } }, { @@ -947,7 +947,7 @@ "script_tags": "get,install,generic,pip-package,generic-python-lib", "script_variations": "package.sympy", "version": "1.13.3", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_cuda,_retinanet,_offline,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_offline,_cuda,_tensorrt,_retinanet,_rtx_4090 )" } }, { @@ -987,7 +987,7 @@ "script_tags": "mlperf,benchmark-mlperf", "script_variations": "", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_cuda,_retinanet,_offline,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_offline,_cuda,_tensorrt,_retinanet,_rtx_4090 )" } } ] diff --git a/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/offline/os_info.json b/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/offline/os_info.json index 1267c343..cca704f3 100644 --- a/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/offline/os_info.json +++ b/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/offline/os_info.json @@ -26,5 +26,5 @@ ], "CM_HOST_PLATFORM_FLAVOR": "x86_64", "CM_HOST_PYTHON_BITS": "64", - "CM_HOST_SYSTEM_NAME": "e891b1c381b6" + "CM_HOST_SYSTEM_NAME": "f77641321894" } \ No newline at end of file diff --git a/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/offline/performance_console.out b/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/offline/performance_console.out index cab83429..8eb74cdf 100644 --- a/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/offline/performance_console.out +++ b/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/offline/performance_console.out @@ -1,8 +1,8 @@ -[2024-12-23 01:53:12,655 main.py:229 INFO] Detected system ID: KnownSystem.RTX4090x2 -[2024-12-23 01:53:12,783 harness.py:249 INFO] The harness will load 2 plugins: ['build/plugins/NMSOptPlugin/libnmsoptplugin.so', 'build/plugins/retinanetConcatPlugin/libretinanetconcatplugin.so'] -[2024-12-23 01:53:12,784 generate_conf_files.py:107 INFO] Generated measurements/ entries for RTX4090x2_TRT/retinanet/Offline -[2024-12-23 01:53:12,784 __init__.py:46 INFO] Running command: ./build/bin/harness_default --plugins="build/plugins/NMSOptPlugin/libnmsoptplugin.so,build/plugins/retinanetConcatPlugin/libretinanetconcatplugin.so" --logfile_outdir="/cm-mount/home/arjun/gh_action_results/valid_results/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/offline/performance/run_1" --logfile_prefix="mlperf_log_" --performance_sample_count=64 --test_mode="PerformanceOnly" --gpu_copy_streams=2 --gpu_inference_streams=2 --use_deque_limit=true --gpu_batch_size=2 --map_path="data_maps/open-images-v6-mlperf/val_map.txt" --mlperf_conf_path="/home/cmuser/CM/repos/local/cache/5860c00d55d14786/inference/mlperf.conf" --tensor_path="build/preprocessed_data/open-images-v6-mlperf/validation/Retinanet/int8_linear" --use_graphs=false --user_conf_path="/home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/ba0e254991d447be85e071d90a1c3226.conf" --gpu_engines="./build/engines/RTX4090x2/retinanet/Offline/retinanet-Offline-gpu-b2-int8.lwis_k_99_MaxP.plan" --max_dlas=0 --scenario Offline --model retinanet --response_postprocess openimageeffnms -[2024-12-23 01:53:12,784 __init__.py:53 INFO] Overriding Environment +[2024-12-25 00:57:27,317 main.py:229 INFO] Detected system ID: KnownSystem.RTX4090x2 +[2024-12-25 00:57:27,444 harness.py:249 INFO] The harness will load 2 plugins: ['build/plugins/NMSOptPlugin/libnmsoptplugin.so', 'build/plugins/retinanetConcatPlugin/libretinanetconcatplugin.so'] +[2024-12-25 00:57:27,445 generate_conf_files.py:107 INFO] Generated measurements/ entries for RTX4090x2_TRT/retinanet/Offline +[2024-12-25 00:57:27,445 __init__.py:46 INFO] Running command: ./build/bin/harness_default --plugins="build/plugins/NMSOptPlugin/libnmsoptplugin.so,build/plugins/retinanetConcatPlugin/libretinanetconcatplugin.so" --logfile_outdir="/cm-mount/home/arjun/gh_action_results/valid_results/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/offline/performance/run_1" --logfile_prefix="mlperf_log_" --performance_sample_count=64 --test_mode="PerformanceOnly" --gpu_copy_streams=2 --gpu_inference_streams=2 --use_deque_limit=true --gpu_batch_size=2 --map_path="data_maps/open-images-v6-mlperf/val_map.txt" --mlperf_conf_path="/home/cmuser/CM/repos/local/cache/5860c00d55d14786/inference/mlperf.conf" --tensor_path="build/preprocessed_data/open-images-v6-mlperf/validation/Retinanet/int8_linear" --use_graphs=false --user_conf_path="/home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/b08d7a688a4a40ff841a6b82bc674dae.conf" --gpu_engines="./build/engines/RTX4090x2/retinanet/Offline/retinanet-Offline-gpu-b2-int8.lwis_k_99_MaxP.plan" --max_dlas=0 --scenario Offline --model retinanet --response_postprocess openimageeffnms +[2024-12-25 00:57:27,445 __init__.py:53 INFO] Overriding Environment benchmark : Benchmark.Retinanet buffer_manager_thread_count : 0 data_dir : /home/cmuser/CM/repos/local/cache/4db00c74da1e44c8/data @@ -11,7 +11,7 @@ gpu_copy_streams : 2 gpu_inference_streams : 2 input_dtype : int8 input_format : linear -log_dir : /home/cmuser/CM/repos/local/cache/94a57f78972843c6/repo/closed/NVIDIA/build/logs/2024.12.23-01.53.11 +log_dir : /home/cmuser/CM/repos/local/cache/94a57f78972843c6/repo/closed/NVIDIA/build/logs/2024.12.25-00.57.26 map_path : data_maps/open-images-v6-mlperf/val_map.txt mlperf_conf_path : /home/cmuser/CM/repos/local/cache/5860c00d55d14786/inference/mlperf.conf offline_expected_qps : 0.0 @@ -23,7 +23,7 @@ tensor_path : build/preprocessed_data/open-images-v6-mlperf/validation/Retinanet test_mode : PerformanceOnly use_deque_limit : True use_graphs : False -user_conf_path : /home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/ba0e254991d447be85e071d90a1c3226.conf +user_conf_path : /home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/b08d7a688a4a40ff841a6b82bc674dae.conf system_id : RTX4090x2 config_name : RTX4090x2_retinanet_Offline workload_setting : WorkloadSetting(HarnessType.LWIS, AccuracyTarget.k_99, PowerSetting.MaxP) @@ -37,19 +37,19 @@ power_limit : None cpu_freq : None &&&& RUNNING Default_Harness # ./build/bin/harness_default [I] mlperf.conf path: /home/cmuser/CM/repos/local/cache/5860c00d55d14786/inference/mlperf.conf -[I] user.conf path: /home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/ba0e254991d447be85e071d90a1c3226.conf +[I] user.conf path: /home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/b08d7a688a4a40ff841a6b82bc674dae.conf Creating QSL. Finished Creating QSL. Setting up SUT. [I] [TRT] Loaded engine size: 73 MiB -[I] [TRT] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +7, GPU +10, now: CPU 128, GPU 883 (MiB) -[I] [TRT] [MemUsageChange] Init cuDNN: CPU +1, GPU +10, now: CPU 129, GPU 893 (MiB) +[I] [TRT] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +6, GPU +10, now: CPU 127, GPU 883 (MiB) +[I] [TRT] [MemUsageChange] Init cuDNN: CPU +2, GPU +10, now: CPU 129, GPU 893 (MiB) [I] [TRT] [MemUsageChange] TensorRT-managed allocation in engine deserialization: CPU +0, GPU +68, now: CPU 0, GPU 68 (MiB) [I] Device:0.GPU: [0] ./build/engines/RTX4090x2/retinanet/Offline/retinanet-Offline-gpu-b2-int8.lwis_k_99_MaxP.plan has been successfully loaded. [I] [TRT] Loaded engine size: 73 MiB [W] [TRT] Using an engine plan file across different models of devices is not recommended and is likely to affect performance or even cause errors. -[I] [TRT] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +6, GPU +10, now: CPU 164, GPU 626 (MiB) -[I] [TRT] [MemUsageChange] Init cuDNN: CPU +1, GPU +10, now: CPU 165, GPU 636 (MiB) +[I] [TRT] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +6, GPU +10, now: CPU 164, GPU 627 (MiB) +[I] [TRT] [MemUsageChange] Init cuDNN: CPU +1, GPU +10, now: CPU 165, GPU 637 (MiB) [I] [TRT] [MemUsageChange] TensorRT-managed allocation in engine deserialization: CPU +1, GPU +69, now: CPU 1, GPU 137 (MiB) [I] Device:1.GPU: [0] ./build/engines/RTX4090x2/retinanet/Offline/retinanet-Offline-gpu-b2-int8.lwis_k_99_MaxP.plan has been successfully loaded. [E] [TRT] 3: [runtime.cpp::~Runtime::401] Error Code 3: API Usage Error (Parameter check failed at: runtime/rt/runtime.cpp::~Runtime::401, condition: mEngineCounter.use_count() == 1 Destroying a runtime before destroying deserialized engines created by the runtime leads to undefined behavior.) @@ -60,17 +60,17 @@ Setting up SUT. [I] [TRT] [MemUsageChange] Init cuDNN: CPU +1, GPU +12, now: CPU 94, GPU 2461 (MiB) [I] [TRT] Could not set default profile 0 for execution context. Profile index must be set explicitly. [I] [TRT] [MemUsageChange] TensorRT-managed allocation in IExecutionContext creation: CPU +1, GPU +1527, now: CPU 2, GPU 3192 (MiB) -[I] [TRT] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +1, GPU +8, now: CPU 95, GPU 648 (MiB) -[I] [TRT] [MemUsageChange] Init cuDNN: CPU +0, GPU +8, now: CPU 95, GPU 656 (MiB) +[I] [TRT] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +1, GPU +8, now: CPU 95, GPU 649 (MiB) +[I] [TRT] [MemUsageChange] Init cuDNN: CPU +0, GPU +8, now: CPU 95, GPU 657 (MiB) [I] [TRT] [MemUsageChange] TensorRT-managed allocation in IExecutionContext creation: CPU +0, GPU +1528, now: CPU 2, GPU 4720 (MiB) -[I] [TRT] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +0, GPU +8, now: CPU 95, GPU 2192 (MiB) -[I] [TRT] [MemUsageChange] Init cuDNN: CPU +1, GPU +12, now: CPU 96, GPU 2204 (MiB) +[I] [TRT] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +1, GPU +8, now: CPU 96, GPU 2193 (MiB) +[I] [TRT] [MemUsageChange] Init cuDNN: CPU +0, GPU +12, now: CPU 96, GPU 2205 (MiB) [I] [TRT] Could not set default profile 0 for execution context. Profile index must be set explicitly. [I] [TRT] [MemUsageChange] TensorRT-managed allocation in IExecutionContext creation: CPU +1, GPU +1528, now: CPU 3, GPU 6248 (MiB) [I] Creating batcher thread: 0 EnableBatcherThreadPerDevice: false Finished setting up SUT. Starting warmup. Running for a minimum of 5 seconds. -Finished warmup. Ran for 5.03294s. +Finished warmup. Ran for 5.03389s. Starting running actual test. ================================================ MLPerf Results Summary @@ -78,7 +78,7 @@ MLPerf Results Summary SUT name : LWIS_Server Scenario : Offline Mode : PerformanceOnly -Samples per second: 1735.67 +Samples per second: 1733.25 Result is : VALID Min duration satisfied : Yes Min queries satisfied : Yes @@ -87,15 +87,15 @@ Result is : VALID ================================================ Additional Stats ================================================ -Min latency (ns) : 10103064 -Max latency (ns) : 652900040708 -Mean latency (ns) : 326059396190 -50.00 percentile latency (ns) : 326072726405 -90.00 percentile latency (ns) : 587467017824 -95.00 percentile latency (ns) : 620190413152 -97.00 percentile latency (ns) : 633278434850 -99.00 percentile latency (ns) : 646359997095 -99.90 percentile latency (ns) : 652246409070 +Min latency (ns) : 9596849 +Max latency (ns) : 653812127205 +Mean latency (ns) : 326581007159 +50.00 percentile latency (ns) : 326492917586 +90.00 percentile latency (ns) : 588415259666 +95.00 percentile latency (ns) : 621117225069 +97.00 percentile latency (ns) : 634197894873 +99.00 percentile latency (ns) : 647279408516 +99.90 percentile latency (ns) : 653160102521 ================================================ Test Parameters Used @@ -125,17 +125,17 @@ No warnings encountered during test. No errors encountered during test. Finished running actual test. Device Device:0.GPU processed: - 283236 batches of size 2 + 283224 batches of size 2 Memcpy Calls: 0 PerSampleCudaMemcpy Calls: 0 - BatchedCudaMemcpy Calls: 283236 + BatchedCudaMemcpy Calls: 283224 Device Device:1.GPU processed: - 283374 batches of size 2 + 283386 batches of size 2 Memcpy Calls: 0 PerSampleCudaMemcpy Calls: 0 - BatchedCudaMemcpy Calls: 283374 + BatchedCudaMemcpy Calls: 283386 &&&& PASSED Default_Harness # ./build/bin/harness_default -[2024-12-23 02:04:11,570 run_harness.py:166 INFO] Result: result_samples_per_second: 1735.67, Result is VALID +[2024-12-25 01:08:27,121 run_harness.py:166 INFO] Result: result_samples_per_second: 1733.25, Result is VALID ======================== Result summaries: ======================== diff --git a/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/offline/system_info.txt b/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/offline/system_info.txt index 49b939df..5da86f44 100644 --- a/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/offline/system_info.txt +++ b/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/offline/system_info.txt @@ -2,10 +2,10 @@ Platform Details ------------------------------------------------------------ 1. uname -a -Linux e891b1c381b6 6.8.0-49-generic #49-Ubuntu SMP PREEMPT_DYNAMIC Mon Nov 4 02:06:24 UTC 2024 x86_64 x86_64 x86_64 GNU/Linux +Linux f77641321894 6.8.0-49-generic #49-Ubuntu SMP PREEMPT_DYNAMIC Mon Nov 4 02:06:24 UTC 2024 x86_64 x86_64 x86_64 GNU/Linux ------------------------------------------------------------ 2. w - 02:04:13 up 12 days, 20:22, 0 users, load average: 1.21, 1.11, 1.02 + 01:08:28 up 14 days, 19:26, 0 users, load average: 1.17, 1.13, 0.93 USER TTY FROM LOGIN@ IDLE JCPU PCPU WHAT ------------------------------------------------------------ 3. Username @@ -40,7 +40,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 2500.000 +cpu MHz : 3500.000 cache size : 46080 KB physical id : 0 siblings : 48 @@ -68,7 +68,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 800.109 +cpu MHz : 3953.193 cache size : 46080 KB physical id : 0 siblings : 48 @@ -96,7 +96,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 800.000 +cpu MHz : 798.358 cache size : 46080 KB physical id : 0 siblings : 48 @@ -124,7 +124,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 4017.610 +cpu MHz : 800.000 cache size : 46080 KB physical id : 0 siblings : 48 @@ -152,7 +152,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 800.000 +cpu MHz : 800.008 cache size : 46080 KB physical id : 0 siblings : 48 @@ -404,7 +404,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 800.000 +cpu MHz : 1097.727 cache size : 46080 KB physical id : 0 siblings : 48 @@ -432,7 +432,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 2197.943 +cpu MHz : 800.000 cache size : 46080 KB physical id : 0 siblings : 48 @@ -516,7 +516,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 800.982 +cpu MHz : 800.000 cache size : 46080 KB physical id : 0 siblings : 48 @@ -544,7 +544,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 800.192 +cpu MHz : 800.000 cache size : 46080 KB physical id : 0 siblings : 48 @@ -572,7 +572,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 1096.434 +cpu MHz : 800.000 cache size : 46080 KB physical id : 0 siblings : 48 @@ -600,7 +600,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 4300.000 +cpu MHz : 1300.000 cache size : 46080 KB physical id : 0 siblings : 48 @@ -628,7 +628,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 800.000 +cpu MHz : 2588.596 cache size : 46080 KB physical id : 0 siblings : 48 @@ -684,7 +684,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 800.000 +cpu MHz : 3400.000 cache size : 46080 KB physical id : 0 siblings : 48 @@ -740,7 +740,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 800.199 +cpu MHz : 800.000 cache size : 46080 KB physical id : 0 siblings : 48 @@ -824,7 +824,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 1498.868 +cpu MHz : 800.000 cache size : 46080 KB physical id : 0 siblings : 48 @@ -1132,7 +1132,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 802.576 +cpu MHz : 800.000 cache size : 46080 KB physical id : 0 siblings : 48 @@ -1160,7 +1160,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 800.000 +cpu MHz : 802.662 cache size : 46080 KB physical id : 0 siblings : 48 @@ -1328,7 +1328,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 800.000 +cpu MHz : 2284.328 cache size : 46080 KB physical id : 0 siblings : 48 @@ -1394,7 +1394,7 @@ CPU family: 6 Model: 143 Model name: Intel(R) Xeon(R) w7-2495X Stepping: 8 -CPU MHz: 1782.444 +CPU MHz: 2600.000 CPU max MHz: 4800.0000 CPU min MHz: 800.0000 BogoMIPS: 4992.00 @@ -1424,49 +1424,49 @@ Flags: fpu vme de pse tsc msr pae mce cx8 apic se available: 1 nodes (0) node 0 cpus: 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 node 0 size: 192709 MB -node 0 free: 16870 MB +node 0 free: 16772 MB node distances: node 0 0: 10 ------------------------------------------------------------ 9. /proc/meminfo MemTotal: 197334532 kB -MemFree: 17275312 kB -MemAvailable: 193158112 kB -Buffers: 450556 kB -Cached: 173554568 kB -SwapCached: 46220 kB -Active: 2783376 kB -Inactive: 171643704 kB -Active(anon): 369604 kB -Inactive(anon): 91752 kB -Active(file): 2413772 kB -Inactive(file): 171551952 kB +MemFree: 17174532 kB +MemAvailable: 192978164 kB +Buffers: 657904 kB +Cached: 171432444 kB +SwapCached: 37400 kB +Active: 4591476 kB +Inactive: 167945512 kB +Active(anon): 466288 kB +Inactive(anon): 18528 kB +Active(file): 4125188 kB +Inactive(file): 167926984 kB Unevictable: 3088 kB Mlocked: 0 kB SwapTotal: 8388604 kB -SwapFree: 7975300 kB +SwapFree: 7980272 kB Zswap: 0 kB Zswapped: 0 kB -Dirty: 316 kB +Dirty: 108 kB Writeback: 0 kB -AnonPages: 414108 kB -Mapped: 341204 kB -Shmem: 39400 kB -KReclaimable: 3689372 kB -Slab: 4690968 kB -SReclaimable: 3689372 kB -SUnreclaim: 1001596 kB -KernelStack: 18048 kB -PageTables: 20796 kB +AnonPages: 442812 kB +Mapped: 337160 kB +Shmem: 38176 kB +KReclaimable: 5523756 kB +Slab: 6676480 kB +SReclaimable: 5523756 kB +SUnreclaim: 1152724 kB +KernelStack: 18320 kB +PageTables: 21384 kB SecPageTables: 0 kB NFS_Unstable: 0 kB Bounce: 0 kB WritebackTmp: 0 kB CommitLimit: 107055868 kB -Committed_AS: 5393988 kB +Committed_AS: 5499840 kB VmallocTotal: 13743895347199 kB -VmallocUsed: 156384 kB +VmallocUsed: 156640 kB VmallocChunk: 0 kB Percpu: 129600 kB HardwareCorrupted: 0 kB @@ -1482,8 +1482,8 @@ HugePages_Rsvd: 0 HugePages_Surp: 0 Hugepagesize: 2048 kB Hugetlb: 0 kB -DirectMap4k: 45442660 kB -DirectMap2M: 152217600 kB +DirectMap4k: 48985700 kB +DirectMap2M: 148674560 kB DirectMap1G: 5242880 kB ------------------------------------------------------------ 10. who -r @@ -1738,16 +1738,16 @@ dev.tty.ldisc_autoload = 1 dev.tty.legacy_tiocsti = 0 fs.aio-max-nr = 65536 fs.aio-nr = 0 -fs.dentry-state = 1395466 1281731 45 0 676847 0 +fs.dentry-state = 1885569 1738619 45 0 959269 0 fs.dir-notify-enable = 1 fs.epoll.max_user_watches = 43912503 fs.fanotify.max_queued_events = 16384 fs.fanotify.max_user_groups = 128 fs.fanotify.max_user_marks = 1048576 fs.file-max = 9223372036854775807 -fs.file-nr = 5696 0 9223372036854775807 -fs.inode-nr = 786140 176959 -fs.inode-state = 786140 176959 0 0 0 0 0 +fs.file-nr = 5984 0 9223372036854775807 +fs.inode-nr = 1246245 456071 +fs.inode-state = 1246245 456071 0 0 0 0 0 fs.inotify.max_queued_events = 16384 fs.inotify.max_user_instances = 128 fs.inotify.max_user_watches = 65536 @@ -1775,7 +1775,7 @@ fs.quota.drops = 0 fs.quota.free_dquots = 0 fs.quota.lookups = 0 fs.quota.reads = 0 -fs.quota.syncs = 1460 +fs.quota.syncs = 1742 fs.quota.writes = 0 fs.suid_dumpable = 2 fs.verity.require_signatures = 0 @@ -1802,7 +1802,7 @@ kernel.ftrace_dump_on_oops = 0 kernel.ftrace_enabled = 1 kernel.hardlockup_all_cpu_backtrace = 0 kernel.hardlockup_panic = 0 -kernel.hostname = e891b1c381b6 +kernel.hostname = f77641321894 kernel.hotplug = kernel.hung_task_all_cpu_backtrace = 0 kernel.hung_task_check_count = 4194304 @@ -1834,7 +1834,7 @@ kernel.msgmnb = 16384 kernel.msgmni = 32000 kernel.ngroups_max = 65536 kernel.nmi_watchdog = 1 -kernel.ns_last_pid = 20057 +kernel.ns_last_pid = 20060 kernel.numa_balancing = 0 kernel.numa_balancing_promote_rate_limit_MBps = 65536 kernel.oops_all_cpu_backtrace = 0 @@ -1865,13 +1865,13 @@ kernel.printk_devkmsg = on kernel.printk_ratelimit = 5 kernel.printk_ratelimit_burst = 10 kernel.pty.max = 4096 -kernel.pty.nr = 8 +kernel.pty.nr = 9 kernel.pty.reserve = 1024 kernel.random.boot_id = 29685405-01e1-41c8-8cf0-dcaddcc1862c kernel.random.entropy_avail = 256 kernel.random.poolsize = 256 kernel.random.urandom_min_reseed_secs = 60 -kernel.random.uuid = bb7daa93-a352-4f38-a4fe-14b36365fe5c +kernel.random.uuid = 439a607a-a948-4ca9-b4f4-ce6e02d70787 kernel.random.write_wakeup_threshold = 256 kernel.randomize_va_space = 2 kernel.real-root-dev = 0 diff --git a/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/offline/user.conf b/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/offline/user.conf index 1ee3e154..063cb16f 100644 --- a/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/offline/user.conf +++ b/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/offline/user.conf @@ -1 +1 @@ -retinanet.Offline.target_qps = 1753.0267000000001 +retinanet.Offline.target_qps = 1750.5825 diff --git a/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/server/README.md b/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/server/README.md index 433b9210..fdb85253 100644 --- a/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/server/README.md +++ b/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/server/README.md @@ -19,7 +19,7 @@ pip install -U cmind cm rm cache -f -cm pull repo mlcommons@mlperf-automations --checkout=225220c7d9bb7e66e5b9a1e1ebfc3e0180fbd094 +cm pull repo mlcommons@mlperf-automations --checkout=a90475d2de72bf0622cebe8d5ca8eb8c9d872fbd cm run script \ --tags=app,mlperf,inference,generic,_nvidia,_retinanet,_tensorrt,_cuda,_valid,_r4.1-dev_default,_server \ @@ -71,7 +71,7 @@ cm run script \ --env.CM_DOCKER_REUSE_EXISTING_CONTAINER=yes \ --env.CM_DOCKER_DETACHED_MODE=yes \ --env.CM_MLPERF_INFERENCE_RESULTS_DIR_=/home/arjun/gh_action_results/valid_results \ - --env.CM_DOCKER_CONTAINER_ID=e891b1c381b6 \ + --env.CM_DOCKER_CONTAINER_ID=f77641321894 \ --env.CM_MLPERF_LOADGEN_COMPLIANCE_TEST=TEST01 \ --add_deps_recursive.compiler.tags=gcc \ --add_deps_recursive.coco2014-original.tags=_full \ @@ -129,7 +129,7 @@ Platform: RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config Model Precision: int8 ### Accuracy Results -`mAP`: `37.338`, Required accuracy for closed division `>= 37.1745` +`mAP`: `37.345`, Required accuracy for closed division `>= 37.1745` ### Performance Results -`Scheduled samples per second`: `1415.0` +`Scheduled samples per second`: `1414.99` diff --git a/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/server/accuracy_console.out b/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/server/accuracy_console.out index 0726809f..2bf98473 100644 --- a/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/server/accuracy_console.out +++ b/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/server/accuracy_console.out @@ -1,9 +1,9 @@ -[2024-12-23 03:11:12,142 main.py:229 INFO] Detected system ID: KnownSystem.RTX4090x2 -[2024-12-23 03:11:12,245 harness.py:249 INFO] The harness will load 2 plugins: ['build/plugins/NMSOptPlugin/libnmsoptplugin.so', 'build/plugins/retinanetConcatPlugin/libretinanetconcatplugin.so'] -[2024-12-23 03:11:12,245 generate_conf_files.py:107 INFO] Generated measurements/ entries for RTX4090x2_TRT/retinanet/Server -[2024-12-23 03:11:12,246 harness.py:326 INFO] Updated LD_PRELOAD: /usr/lib/x86_64-linux-gnu/libjemalloc.so.2 -[2024-12-23 03:11:12,246 __init__.py:46 INFO] Running command: ./build/bin/harness_default --plugins="build/plugins/NMSOptPlugin/libnmsoptplugin.so,build/plugins/retinanetConcatPlugin/libretinanetconcatplugin.so" --logfile_outdir="/cm-mount/home/arjun/gh_action_results/valid_results/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/server/accuracy" --logfile_prefix="mlperf_log_" --performance_sample_count=64 --test_mode="AccuracyOnly" --gpu_copy_streams=2 --gpu_inference_streams=2 --use_cuda_thread_per_device=true --use_deque_limit=true --gpu_batch_size=8 --map_path="data_maps/open-images-v6-mlperf/val_map.txt" --mlperf_conf_path="/home/cmuser/CM/repos/local/cache/5860c00d55d14786/inference/mlperf.conf" --tensor_path="build/preprocessed_data/open-images-v6-mlperf/validation/Retinanet/int8_linear" --use_graphs=false --user_conf_path="/home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/aff437e6870b43fab92958d8945f61bf.conf" --gpu_engines="./build/engines/RTX4090x2/retinanet/Server/retinanet-Server-gpu-b8-int8.lwis_k_99_MaxP.plan" --max_dlas=0 --scenario Server --model retinanet --response_postprocess openimageeffnms -[2024-12-23 03:11:12,246 __init__.py:53 INFO] Overriding Environment +[2024-12-25 02:15:42,365 main.py:229 INFO] Detected system ID: KnownSystem.RTX4090x2 +[2024-12-25 02:15:42,463 harness.py:249 INFO] The harness will load 2 plugins: ['build/plugins/NMSOptPlugin/libnmsoptplugin.so', 'build/plugins/retinanetConcatPlugin/libretinanetconcatplugin.so'] +[2024-12-25 02:15:42,463 generate_conf_files.py:107 INFO] Generated measurements/ entries for RTX4090x2_TRT/retinanet/Server +[2024-12-25 02:15:42,463 harness.py:326 INFO] Updated LD_PRELOAD: /usr/lib/x86_64-linux-gnu/libjemalloc.so.2 +[2024-12-25 02:15:42,463 __init__.py:46 INFO] Running command: ./build/bin/harness_default --plugins="build/plugins/NMSOptPlugin/libnmsoptplugin.so,build/plugins/retinanetConcatPlugin/libretinanetconcatplugin.so" --logfile_outdir="/cm-mount/home/arjun/gh_action_results/valid_results/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/server/accuracy" --logfile_prefix="mlperf_log_" --performance_sample_count=64 --test_mode="AccuracyOnly" --gpu_copy_streams=2 --gpu_inference_streams=2 --use_cuda_thread_per_device=true --use_deque_limit=true --gpu_batch_size=8 --map_path="data_maps/open-images-v6-mlperf/val_map.txt" --mlperf_conf_path="/home/cmuser/CM/repos/local/cache/5860c00d55d14786/inference/mlperf.conf" --tensor_path="build/preprocessed_data/open-images-v6-mlperf/validation/Retinanet/int8_linear" --use_graphs=false --user_conf_path="/home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/f85482eb2d4347fea903fb03ebc6662e.conf" --gpu_engines="./build/engines/RTX4090x2/retinanet/Server/retinanet-Server-gpu-b8-int8.lwis_k_99_MaxP.plan" --max_dlas=0 --scenario Server --model retinanet --response_postprocess openimageeffnms +[2024-12-25 02:15:42,463 __init__.py:53 INFO] Overriding Environment ERROR: ld.so: object '/usr/lib/x86_64-linux-gnu/libjemalloc.so.2' from LD_PRELOAD cannot be preloaded (cannot open shared object file): ignored. ERROR: ld.so: object '/usr/lib/x86_64-linux-gnu/libjemalloc.so.2' from LD_PRELOAD cannot be preloaded (cannot open shared object file): ignored. benchmark : Benchmark.Retinanet @@ -14,7 +14,7 @@ gpu_copy_streams : 2 gpu_inference_streams : 2 input_dtype : int8 input_format : linear -log_dir : /home/cmuser/CM/repos/local/cache/94a57f78972843c6/repo/closed/NVIDIA/build/logs/2024.12.23-03.11.10 +log_dir : /home/cmuser/CM/repos/local/cache/94a57f78972843c6/repo/closed/NVIDIA/build/logs/2024.12.25-02.15.40 map_path : data_maps/open-images-v6-mlperf/val_map.txt mlperf_conf_path : /home/cmuser/CM/repos/local/cache/5860c00d55d14786/inference/mlperf.conf precision : int8 @@ -28,7 +28,7 @@ test_mode : AccuracyOnly use_cuda_thread_per_device : True use_deque_limit : True use_graphs : False -user_conf_path : /home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/aff437e6870b43fab92958d8945f61bf.conf +user_conf_path : /home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/f85482eb2d4347fea903fb03ebc6662e.conf system_id : RTX4090x2 config_name : RTX4090x2_retinanet_Server workload_setting : WorkloadSetting(HarnessType.LWIS, AccuracyTarget.k_99, PowerSetting.MaxP) @@ -42,34 +42,34 @@ power_limit : None cpu_freq : None &&&& RUNNING Default_Harness # ./build/bin/harness_default [I] mlperf.conf path: /home/cmuser/CM/repos/local/cache/5860c00d55d14786/inference/mlperf.conf -[I] user.conf path: /home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/aff437e6870b43fab92958d8945f61bf.conf +[I] user.conf path: /home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/f85482eb2d4347fea903fb03ebc6662e.conf Creating QSL. Finished Creating QSL. Setting up SUT. -[I] [TRT] Loaded engine size: 74 MiB -[I] [TRT] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +6, GPU +10, now: CPU 128, GPU 883 (MiB) -[I] [TRT] [MemUsageChange] Init cuDNN: CPU +2, GPU +10, now: CPU 130, GPU 893 (MiB) +[I] [TRT] Loaded engine size: 73 MiB +[I] [TRT] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +6, GPU +10, now: CPU 127, GPU 881 (MiB) +[I] [TRT] [MemUsageChange] Init cuDNN: CPU +2, GPU +10, now: CPU 129, GPU 891 (MiB) [I] [TRT] [MemUsageChange] TensorRT-managed allocation in engine deserialization: CPU +0, GPU +68, now: CPU 0, GPU 68 (MiB) [I] Device:0.GPU: [0] ./build/engines/RTX4090x2/retinanet/Server/retinanet-Server-gpu-b8-int8.lwis_k_99_MaxP.plan has been successfully loaded. -[I] [TRT] Loaded engine size: 74 MiB +[I] [TRT] Loaded engine size: 73 MiB [W] [TRT] Using an engine plan file across different models of devices is not recommended and is likely to affect performance or even cause errors. -[I] [TRT] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +7, GPU +10, now: CPU 165, GPU 627 (MiB) -[I] [TRT] [MemUsageChange] Init cuDNN: CPU +1, GPU +10, now: CPU 166, GPU 637 (MiB) +[I] [TRT] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +6, GPU +10, now: CPU 163, GPU 625 (MiB) +[I] [TRT] [MemUsageChange] Init cuDNN: CPU +1, GPU +10, now: CPU 164, GPU 635 (MiB) [I] [TRT] [MemUsageChange] TensorRT-managed allocation in engine deserialization: CPU +1, GPU +69, now: CPU 1, GPU 137 (MiB) [I] Device:1.GPU: [0] ./build/engines/RTX4090x2/retinanet/Server/retinanet-Server-gpu-b8-int8.lwis_k_99_MaxP.plan has been successfully loaded. [E] [TRT] 3: [runtime.cpp::~Runtime::401] Error Code 3: API Usage Error (Parameter check failed at: runtime/rt/runtime.cpp::~Runtime::401, condition: mEngineCounter.use_count() == 1 Destroying a runtime before destroying deserialized engines created by the runtime leads to undefined behavior.) -[I] [TRT] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +0, GPU +8, now: CPU 93, GPU 905 (MiB) -[I] [TRT] [MemUsageChange] Init cuDNN: CPU +0, GPU +8, now: CPU 93, GPU 913 (MiB) +[I] [TRT] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +0, GPU +8, now: CPU 91, GPU 903 (MiB) +[I] [TRT] [MemUsageChange] Init cuDNN: CPU +1, GPU +8, now: CPU 92, GPU 911 (MiB) [I] [TRT] [MemUsageChange] TensorRT-managed allocation in IExecutionContext creation: CPU +0, GPU +6111, now: CPU 1, GPU 6248 (MiB) -[I] [TRT] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +0, GPU +8, now: CPU 94, GPU 7033 (MiB) -[I] [TRT] [MemUsageChange] Init cuDNN: CPU +0, GPU +12, now: CPU 94, GPU 7045 (MiB) +[I] [TRT] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +0, GPU +8, now: CPU 92, GPU 7031 (MiB) +[I] [TRT] [MemUsageChange] Init cuDNN: CPU +1, GPU +12, now: CPU 93, GPU 7043 (MiB) [I] [TRT] Could not set default profile 0 for execution context. Profile index must be set explicitly. [I] [TRT] [MemUsageChange] TensorRT-managed allocation in IExecutionContext creation: CPU +1, GPU +6111, now: CPU 2, GPU 12359 (MiB) -[I] [TRT] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +0, GPU +8, now: CPU 95, GPU 649 (MiB) -[I] [TRT] [MemUsageChange] Init cuDNN: CPU +0, GPU +8, now: CPU 95, GPU 657 (MiB) +[I] [TRT] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +0, GPU +8, now: CPU 94, GPU 647 (MiB) +[I] [TRT] [MemUsageChange] Init cuDNN: CPU +0, GPU +8, now: CPU 94, GPU 655 (MiB) [I] [TRT] [MemUsageChange] TensorRT-managed allocation in IExecutionContext creation: CPU +0, GPU +6111, now: CPU 2, GPU 18470 (MiB) -[I] [TRT] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +0, GPU +8, now: CPU 96, GPU 6777 (MiB) -[I] [TRT] [MemUsageChange] Init cuDNN: CPU +1, GPU +12, now: CPU 97, GPU 6789 (MiB) +[I] [TRT] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +0, GPU +8, now: CPU 95, GPU 6775 (MiB) +[I] [TRT] [MemUsageChange] Init cuDNN: CPU +0, GPU +12, now: CPU 95, GPU 6787 (MiB) [I] [TRT] Could not set default profile 0 for execution context. Profile index must be set explicitly. [I] [TRT] [MemUsageChange] TensorRT-managed allocation in IExecutionContext creation: CPU +1, GPU +6111, now: CPU 3, GPU 24581 (MiB) [I] Creating batcher thread: 0 EnableBatcherThreadPerDevice: false @@ -77,7 +77,7 @@ Setting up SUT. [I] Creating cuda thread: 1 Finished setting up SUT. Starting warmup. Running for a minimum of 5 seconds. -Finished warmup. Ran for 5.12994s. +Finished warmup. Ran for 5.16111s. Starting running actual test. No warnings encountered during test. @@ -85,45 +85,45 @@ No warnings encountered during test. No errors encountered during test. Finished running actual test. Device Device:0.GPU processed: - 29 batches of size 1 - 35 batches of size 2 - 47 batches of size 3 + 24 batches of size 1 + 29 batches of size 2 + 48 batches of size 3 22 batches of size 4 - 46 batches of size 5 - 34 batches of size 6 - 29 batches of size 7 - 1429 batches of size 8 + 50 batches of size 5 + 29 batches of size 6 + 24 batches of size 7 + 1436 batches of size 8 Memcpy Calls: 0 - PerSampleCudaMemcpy Calls: 12368 - BatchedCudaMemcpy Calls: 29 + PerSampleCudaMemcpy Calls: 12370 + BatchedCudaMemcpy Calls: 24 Device Device:1.GPU processed: - 33 batches of size 1 - 30 batches of size 2 - 51 batches of size 3 - 14 batches of size 4 - 51 batches of size 5 - 30 batches of size 6 - 33 batches of size 7 - 1427 batches of size 8 + 29 batches of size 1 + 24 batches of size 2 + 50 batches of size 3 + 20 batches of size 4 + 49 batches of size 5 + 24 batches of size 6 + 29 batches of size 7 + 1436 batches of size 8 Memcpy Calls: 0 - PerSampleCudaMemcpy Calls: 12351 - BatchedCudaMemcpy Calls: 33 + PerSampleCudaMemcpy Calls: 12358 + BatchedCudaMemcpy Calls: 29 &&&& PASSED Default_Harness # ./build/bin/harness_default -[2024-12-23 03:11:53,963 run_harness.py:166 INFO] Result: Accuracy run detected. -[2024-12-23 03:11:53,963 __init__.py:46 INFO] Running command: python3 /home/cmuser/CM/repos/local/cache/94a57f78972843c6/repo/closed/NVIDIA/build/inference/vision/classification_and_detection/tools/accuracy-openimages.py --mlperf-accuracy-file /cm-mount/home/arjun/gh_action_results/valid_results/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/server/accuracy/mlperf_log_accuracy.json --openimages-dir /home/cmuser/CM/repos/local/cache/4db00c74da1e44c8/preprocessed_data/open-images-v6-mlperf --output-file build/retinanet-results.json +[2024-12-25 02:16:24,266 run_harness.py:166 INFO] Result: Accuracy run detected. +[2024-12-25 02:16:24,267 __init__.py:46 INFO] Running command: python3 /home/cmuser/CM/repos/local/cache/94a57f78972843c6/repo/closed/NVIDIA/build/inference/vision/classification_and_detection/tools/accuracy-openimages.py --mlperf-accuracy-file /cm-mount/home/arjun/gh_action_results/valid_results/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/server/accuracy/mlperf_log_accuracy.json --openimages-dir /home/cmuser/CM/repos/local/cache/4db00c74da1e44c8/preprocessed_data/open-images-v6-mlperf --output-file build/retinanet-results.json loading annotations into memory... -Done (t=0.52s) +Done (t=0.53s) creating index... index created! Loading and preparing results... -DONE (t=17.86s) +DONE (t=17.70s) creating index... index created! Running per image evaluation... Evaluate annotation type *bbox* -DONE (t=132.65s). +DONE (t=134.04s). Accumulating evaluation results... -DONE (t=32.32s). +DONE (t=33.18s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.373 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.522 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.404 @@ -133,10 +133,10 @@ DONE (t=32.32s). Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.419 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.599 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.628 - Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.081 + Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.082 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.344 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.678 -mAP=37.338% +mAP=37.345% ======================== Result summaries: ======================== diff --git a/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/server/cm-deps.mmd b/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/server/cm-deps.mmd index 02ef2f7a..bca6c9ed 100644 --- a/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/server/cm-deps.mmd +++ b/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/server/cm-deps.mmd @@ -14,19 +14,19 @@ graph TD get-generic-python-lib,94b62a682bc44791_(_package.numpy_) --> get,python3 get-cuda-devices,7a3ede4d3558427a_(_with-pycuda_) --> get,generic-python-lib,_package.numpy app-mlperf-inference,d775cac873ee4231_(_nvidia,_retinanet,_tensorrt,_cuda,_valid,_r4.1-dev_default,_server_) --> get,cuda-devices,_with-pycuda - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_retinanet,_server,_cuda,_tensorrt,_rtx_4090_) --> detect,os + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_server,_retinanet,_cuda,_rtx_4090_) --> detect,os detect-cpu,586c8a43320142f7 --> detect,os - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_retinanet,_server,_cuda,_tensorrt,_rtx_4090_) --> detect,cpu - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_retinanet,_server,_cuda,_tensorrt,_rtx_4090_) --> get,sys-utils-cm - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_retinanet,_server,_cuda,_tensorrt,_rtx_4090_) --> get,mlperf,inference,nvidia,scratch,space + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_server,_retinanet,_cuda,_rtx_4090_) --> detect,cpu + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_server,_retinanet,_cuda,_rtx_4090_) --> get,sys-utils-cm + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_server,_retinanet,_cuda,_rtx_4090_) --> get,mlperf,inference,nvidia,scratch,space get-generic-python-lib,94b62a682bc44791_(_mlperf_logging_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_retinanet,_server,_cuda,_tensorrt,_rtx_4090_) --> get,generic-python-lib,_mlperf_logging - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_retinanet,_server,_cuda,_tensorrt,_rtx_4090_) --> get,dataset,original,openimages,_validation,_full,_custom-annotations - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_retinanet,_server,_cuda,_tensorrt,_rtx_4090_) --> get,dataset,original,openimages,_calibration - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_retinanet,_server,_cuda,_tensorrt,_rtx_4090_) --> get,mlcommons,inference,src - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_retinanet,_server,_cuda,_tensorrt,_rtx_4090_) --> get,nvidia,mlperf,inference,common-code,_mlcommons + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_server,_retinanet,_cuda,_rtx_4090_) --> get,generic-python-lib,_mlperf_logging + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_server,_retinanet,_cuda,_rtx_4090_) --> get,dataset,original,openimages,_validation,_full,_custom-annotations + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_server,_retinanet,_cuda,_rtx_4090_) --> get,dataset,original,openimages,_calibration + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_server,_retinanet,_cuda,_rtx_4090_) --> get,mlcommons,inference,src + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_server,_retinanet,_cuda,_rtx_4090_) --> get,nvidia,mlperf,inference,common-code,_mlcommons pull-git-repo,c23132ed65c4421d --> detect,os - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_retinanet,_server,_cuda,_tensorrt,_rtx_4090_) --> pull,git,repo + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_server,_retinanet,_cuda,_rtx_4090_) --> pull,git,repo generate-mlperf-inference-user-conf,3af4475745964b93 --> detect,os detect-cpu,586c8a43320142f7 --> detect,os generate-mlperf-inference-user-conf,3af4475745964b93 --> detect,cpu @@ -34,163 +34,163 @@ graph TD generate-mlperf-inference-user-conf,3af4475745964b93 --> get,mlcommons,inference,src get-mlperf-inference-sut-configs,c2fbf72009e2445b --> get,cache,dir,_name.mlperf-inference-sut-configs generate-mlperf-inference-user-conf,3af4475745964b93 --> get,sut,configs - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_retinanet,_server,_cuda,_tensorrt,_rtx_4090_) --> generate,user-conf,mlperf,inference + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_server,_retinanet,_cuda,_rtx_4090_) --> generate,user-conf,mlperf,inference get-generic-python-lib,94b62a682bc44791_(_package.pycuda_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_retinanet,_server,_cuda,_tensorrt,_rtx_4090_) --> get,generic-python-lib,_package.pycuda - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_retinanet,_server,_cuda,_tensorrt,_rtx_4090_) --> get,nvidia,mitten - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_retinanet,_server,_cuda,_tensorrt,_rtx_4090_) --> get,cuda,_cudnn - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_retinanet,_server,_cuda,_tensorrt,_rtx_4090_) --> get,tensorrt - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_retinanet,_server,_cuda,_tensorrt,_rtx_4090_) --> build,nvidia,inference,server,_mlcommons - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_retinanet,_server,_cuda,_tensorrt,_batch_size.8,_batch_size.2,_v4.1-dev_) --> detect,os + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_server,_retinanet,_cuda,_rtx_4090_) --> get,generic-python-lib,_package.pycuda + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_server,_retinanet,_cuda,_rtx_4090_) --> get,nvidia,mitten + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_server,_retinanet,_cuda,_rtx_4090_) --> get,cuda,_cudnn + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_server,_retinanet,_cuda,_rtx_4090_) --> get,tensorrt + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_server,_retinanet,_cuda,_rtx_4090_) --> build,nvidia,inference,server,_mlcommons + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_server,_retinanet,_cuda,_batch_size.8,_batch_size.2,_v4.1-dev_) --> detect,os detect-cpu,586c8a43320142f7 --> detect,os - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_retinanet,_server,_cuda,_tensorrt,_batch_size.8,_batch_size.2,_v4.1-dev_) --> detect,cpu - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_retinanet,_server,_cuda,_tensorrt,_batch_size.8,_batch_size.2,_v4.1-dev_) --> get,sys-utils-cm - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_retinanet,_server,_cuda,_tensorrt,_batch_size.8,_batch_size.2,_v4.1-dev_) --> get,mlperf,inference,nvidia,scratch,space,_version.4_0 + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_server,_retinanet,_cuda,_batch_size.8,_batch_size.2,_v4.1-dev_) --> detect,cpu + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_server,_retinanet,_cuda,_batch_size.8,_batch_size.2,_v4.1-dev_) --> get,sys-utils-cm + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_server,_retinanet,_cuda,_batch_size.8,_batch_size.2,_v4.1-dev_) --> get,mlperf,inference,nvidia,scratch,space,_version.4_0 get-generic-python-lib,94b62a682bc44791_(_mlperf_logging_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_retinanet,_server,_cuda,_tensorrt,_batch_size.8,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_mlperf_logging - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_retinanet,_server,_cuda,_tensorrt,_batch_size.8,_batch_size.2,_v4.1-dev_) --> get,dataset,original,openimages,_validation,_full,_custom-annotations - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_retinanet,_server,_cuda,_tensorrt,_batch_size.8,_batch_size.2,_v4.1-dev_) --> get,dataset,original,openimages,_calibration - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_retinanet,_server,_cuda,_tensorrt,_batch_size.8,_batch_size.2,_v4.1-dev_) --> get,mlcommons,inference,src - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_retinanet,_server,_cuda,_tensorrt,_batch_size.8,_batch_size.2,_v4.1-dev_) --> get,nvidia,mlperf,inference,common-code,_mlcommons + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_server,_retinanet,_cuda,_batch_size.8,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_mlperf_logging + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_server,_retinanet,_cuda,_batch_size.8,_batch_size.2,_v4.1-dev_) --> get,dataset,original,openimages,_validation,_full,_custom-annotations + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_server,_retinanet,_cuda,_batch_size.8,_batch_size.2,_v4.1-dev_) --> get,dataset,original,openimages,_calibration + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_server,_retinanet,_cuda,_batch_size.8,_batch_size.2,_v4.1-dev_) --> get,mlcommons,inference,src + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_server,_retinanet,_cuda,_batch_size.8,_batch_size.2,_v4.1-dev_) --> get,nvidia,mlperf,inference,common-code,_mlcommons pull-git-repo,c23132ed65c4421d --> detect,os - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_retinanet,_server,_cuda,_tensorrt,_batch_size.8,_batch_size.2,_v4.1-dev_) --> pull,git,repo + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_server,_retinanet,_cuda,_batch_size.8,_batch_size.2,_v4.1-dev_) --> pull,git,repo get-generic-python-lib,94b62a682bc44791_(_package.pycuda_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_retinanet,_server,_cuda,_tensorrt,_batch_size.8,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_package.pycuda - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_retinanet,_server,_cuda,_tensorrt,_batch_size.8,_batch_size.2,_v4.1-dev_) --> get,nvidia,mitten - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_retinanet,_server,_cuda,_tensorrt,_batch_size.8,_batch_size.2,_v4.1-dev_) --> get,cuda,_cudnn - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_retinanet,_server,_cuda,_tensorrt,_batch_size.8,_batch_size.2,_v4.1-dev_) --> get,tensorrt - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_retinanet,_server,_cuda,_tensorrt,_batch_size.8,_batch_size.2,_v4.1-dev_) --> build,nvidia,inference,server,_mlcommons - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_retinanet,_cuda,_tensorrt,_batch_size.2,_v4.1-dev_) --> detect,os + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_server,_retinanet,_cuda,_batch_size.8,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_package.pycuda + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_server,_retinanet,_cuda,_batch_size.8,_batch_size.2,_v4.1-dev_) --> get,nvidia,mitten + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_server,_retinanet,_cuda,_batch_size.8,_batch_size.2,_v4.1-dev_) --> get,cuda,_cudnn + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_server,_retinanet,_cuda,_batch_size.8,_batch_size.2,_v4.1-dev_) --> get,tensorrt + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_server,_retinanet,_cuda,_batch_size.8,_batch_size.2,_v4.1-dev_) --> build,nvidia,inference,server,_mlcommons + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_tensorrt,_retinanet,_cuda,_batch_size.2,_v4.1-dev_) --> detect,os detect-cpu,586c8a43320142f7 --> detect,os - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_retinanet,_cuda,_tensorrt,_batch_size.2,_v4.1-dev_) --> detect,cpu - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_retinanet,_cuda,_tensorrt,_batch_size.2,_v4.1-dev_) --> get,sys-utils-cm - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_retinanet,_cuda,_tensorrt,_batch_size.2,_v4.1-dev_) --> get,mlperf,inference,nvidia,scratch,space,_version.4_0 + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_tensorrt,_retinanet,_cuda,_batch_size.2,_v4.1-dev_) --> detect,cpu + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_tensorrt,_retinanet,_cuda,_batch_size.2,_v4.1-dev_) --> get,sys-utils-cm + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_tensorrt,_retinanet,_cuda,_batch_size.2,_v4.1-dev_) --> get,mlperf,inference,nvidia,scratch,space,_version.4_0 get-generic-python-lib,94b62a682bc44791_(_mlperf_logging_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_retinanet,_cuda,_tensorrt,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_mlperf_logging - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_retinanet,_cuda,_tensorrt,_batch_size.2,_v4.1-dev_) --> get,dataset,original,openimages,_validation,_full,_custom-annotations - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_retinanet,_cuda,_tensorrt,_batch_size.2,_v4.1-dev_) --> get,dataset,original,openimages,_calibration - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_retinanet,_cuda,_tensorrt,_batch_size.2,_v4.1-dev_) --> get,mlcommons,inference,src - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_retinanet,_cuda,_tensorrt,_batch_size.2,_v4.1-dev_) --> get,nvidia,mlperf,inference,common-code,_mlcommons + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_tensorrt,_retinanet,_cuda,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_mlperf_logging + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_tensorrt,_retinanet,_cuda,_batch_size.2,_v4.1-dev_) --> get,dataset,original,openimages,_validation,_full,_custom-annotations + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_tensorrt,_retinanet,_cuda,_batch_size.2,_v4.1-dev_) --> get,dataset,original,openimages,_calibration + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_tensorrt,_retinanet,_cuda,_batch_size.2,_v4.1-dev_) --> get,mlcommons,inference,src + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_tensorrt,_retinanet,_cuda,_batch_size.2,_v4.1-dev_) --> get,nvidia,mlperf,inference,common-code,_mlcommons pull-git-repo,c23132ed65c4421d --> detect,os - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_retinanet,_cuda,_tensorrt,_batch_size.2,_v4.1-dev_) --> pull,git,repo + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_tensorrt,_retinanet,_cuda,_batch_size.2,_v4.1-dev_) --> pull,git,repo get-generic-python-lib,94b62a682bc44791_(_package.pycuda_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_retinanet,_cuda,_tensorrt,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_package.pycuda - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_retinanet,_cuda,_tensorrt,_batch_size.2,_v4.1-dev_) --> get,nvidia,mitten + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_tensorrt,_retinanet,_cuda,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_package.pycuda + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_tensorrt,_retinanet,_cuda,_batch_size.2,_v4.1-dev_) --> get,nvidia,mitten get-generic-python-lib,94b62a682bc44791_(_Pillow_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_retinanet,_cuda,_tensorrt,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_Pillow + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_tensorrt,_retinanet,_cuda,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_Pillow get-generic-python-lib,94b62a682bc44791_(_opencv-python_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_retinanet,_cuda,_tensorrt,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_opencv-python + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_tensorrt,_retinanet,_cuda,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_opencv-python get-generic-python-lib,94b62a682bc44791_(_numpy_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_retinanet,_cuda,_tensorrt,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_numpy + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_tensorrt,_retinanet,_cuda,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_numpy get-generic-python-lib,94b62a682bc44791_(_pycocotools_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_retinanet,_cuda,_tensorrt,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_pycocotools + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_tensorrt,_retinanet,_cuda,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_pycocotools get-generic-python-lib,94b62a682bc44791_(_onnx-graphsurgeon_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_retinanet,_cuda,_tensorrt,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_onnx-graphsurgeon + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_tensorrt,_retinanet,_cuda,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_onnx-graphsurgeon get-generic-python-lib,94b62a682bc44791_(_package.onnx_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_retinanet,_cuda,_tensorrt,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_package.onnx + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_tensorrt,_retinanet,_cuda,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_package.onnx get-generic-python-lib,94b62a682bc44791_(_package.sympy_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_retinanet,_cuda,_tensorrt,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_package.sympy - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_retinanet,_cuda,_tensorrt,_batch_size.2,_v4.1-dev_) --> save,mlperf,inference,state - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_retinanet,_server,_cuda,_tensorrt,_batch_size.8,_batch_size.2,_v4.1-dev_) --> reproduce,mlperf,inference,nvidia,harness,_preprocess_data,_retinanet,_cuda,_tensorrt,_batch_size.2,_v4.1-dev - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_download_model,_retinanet,_cuda,_tensorrt,_batch_size.2,_v4.1-dev_) --> detect,os + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_tensorrt,_retinanet,_cuda,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_package.sympy + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_tensorrt,_retinanet,_cuda,_batch_size.2,_v4.1-dev_) --> save,mlperf,inference,state + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_server,_retinanet,_cuda,_batch_size.8,_batch_size.2,_v4.1-dev_) --> reproduce,mlperf,inference,nvidia,harness,_preprocess_data,_tensorrt,_retinanet,_cuda,_batch_size.2,_v4.1-dev + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_download_model,_tensorrt,_retinanet,_cuda,_batch_size.2,_v4.1-dev_) --> detect,os detect-cpu,586c8a43320142f7 --> detect,os - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_download_model,_retinanet,_cuda,_tensorrt,_batch_size.2,_v4.1-dev_) --> detect,cpu - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_download_model,_retinanet,_cuda,_tensorrt,_batch_size.2,_v4.1-dev_) --> get,sys-utils-cm - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_download_model,_retinanet,_cuda,_tensorrt,_batch_size.2,_v4.1-dev_) --> get,mlperf,inference,nvidia,scratch,space,_version.4_0 + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_download_model,_tensorrt,_retinanet,_cuda,_batch_size.2,_v4.1-dev_) --> detect,cpu + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_download_model,_tensorrt,_retinanet,_cuda,_batch_size.2,_v4.1-dev_) --> get,sys-utils-cm + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_download_model,_tensorrt,_retinanet,_cuda,_batch_size.2,_v4.1-dev_) --> get,mlperf,inference,nvidia,scratch,space,_version.4_0 get-generic-python-lib,94b62a682bc44791_(_mlperf_logging_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_download_model,_retinanet,_cuda,_tensorrt,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_mlperf_logging - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_download_model,_retinanet,_cuda,_tensorrt,_batch_size.2,_v4.1-dev_) --> get,dataset,original,openimages,_validation,_full,_custom-annotations - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_download_model,_retinanet,_cuda,_tensorrt,_batch_size.2,_v4.1-dev_) --> get,dataset,original,openimages,_calibration - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_download_model,_retinanet,_cuda,_tensorrt,_batch_size.2,_v4.1-dev_) --> get,mlcommons,inference,src - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_download_model,_retinanet,_cuda,_tensorrt,_batch_size.2,_v4.1-dev_) --> get,nvidia,mlperf,inference,common-code,_mlcommons + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_download_model,_tensorrt,_retinanet,_cuda,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_mlperf_logging + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_download_model,_tensorrt,_retinanet,_cuda,_batch_size.2,_v4.1-dev_) --> get,dataset,original,openimages,_validation,_full,_custom-annotations + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_download_model,_tensorrt,_retinanet,_cuda,_batch_size.2,_v4.1-dev_) --> get,dataset,original,openimages,_calibration + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_download_model,_tensorrt,_retinanet,_cuda,_batch_size.2,_v4.1-dev_) --> get,mlcommons,inference,src + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_download_model,_tensorrt,_retinanet,_cuda,_batch_size.2,_v4.1-dev_) --> get,nvidia,mlperf,inference,common-code,_mlcommons pull-git-repo,c23132ed65c4421d --> detect,os - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_download_model,_retinanet,_cuda,_tensorrt,_batch_size.2,_v4.1-dev_) --> pull,git,repo + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_download_model,_tensorrt,_retinanet,_cuda,_batch_size.2,_v4.1-dev_) --> pull,git,repo get-generic-python-lib,94b62a682bc44791_(_package.pycuda_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_download_model,_retinanet,_cuda,_tensorrt,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_package.pycuda - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_download_model,_retinanet,_cuda,_tensorrt,_batch_size.2,_v4.1-dev_) --> get,nvidia,mitten + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_download_model,_tensorrt,_retinanet,_cuda,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_package.pycuda + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_download_model,_tensorrt,_retinanet,_cuda,_batch_size.2,_v4.1-dev_) --> get,nvidia,mitten get-generic-python-lib,94b62a682bc44791_(_torch_cuda_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_download_model,_retinanet,_cuda,_tensorrt,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_torch_cuda + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_download_model,_tensorrt,_retinanet,_cuda,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_torch_cuda get-generic-python-lib,94b62a682bc44791_(_Pillow_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_download_model,_retinanet,_cuda,_tensorrt,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_Pillow + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_download_model,_tensorrt,_retinanet,_cuda,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_Pillow get-generic-python-lib,94b62a682bc44791_(_opencv-python_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_download_model,_retinanet,_cuda,_tensorrt,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_opencv-python + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_download_model,_tensorrt,_retinanet,_cuda,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_opencv-python get-generic-python-lib,94b62a682bc44791_(_numpy_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_download_model,_retinanet,_cuda,_tensorrt,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_numpy + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_download_model,_tensorrt,_retinanet,_cuda,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_numpy get-generic-python-lib,94b62a682bc44791_(_pycocotools_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_download_model,_retinanet,_cuda,_tensorrt,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_pycocotools + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_download_model,_tensorrt,_retinanet,_cuda,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_pycocotools get-generic-python-lib,94b62a682bc44791_(_onnx-graphsurgeon_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_download_model,_retinanet,_cuda,_tensorrt,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_onnx-graphsurgeon + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_download_model,_tensorrt,_retinanet,_cuda,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_onnx-graphsurgeon get-generic-python-lib,94b62a682bc44791_(_package.onnx_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_download_model,_retinanet,_cuda,_tensorrt,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_package.onnx + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_download_model,_tensorrt,_retinanet,_cuda,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_package.onnx get-generic-python-lib,94b62a682bc44791_(_package.sympy_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_download_model,_retinanet,_cuda,_tensorrt,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_package.sympy - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_download_model,_retinanet,_cuda,_tensorrt,_batch_size.2,_v4.1-dev_) --> save,mlperf,inference,state - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_retinanet,_server,_cuda,_tensorrt,_batch_size.8,_batch_size.2,_v4.1-dev_) --> reproduce,mlperf,inference,nvidia,harness,_download_model,_retinanet,_cuda,_tensorrt,_batch_size.2,_v4.1-dev - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_calibrate,_retinanet,_cuda,_tensorrt,_batch_size.2,_v4.1-dev_) --> detect,os + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_download_model,_tensorrt,_retinanet,_cuda,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_package.sympy + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_download_model,_tensorrt,_retinanet,_cuda,_batch_size.2,_v4.1-dev_) --> save,mlperf,inference,state + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_server,_retinanet,_cuda,_batch_size.8,_batch_size.2,_v4.1-dev_) --> reproduce,mlperf,inference,nvidia,harness,_download_model,_tensorrt,_retinanet,_cuda,_batch_size.2,_v4.1-dev + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_calibrate,_tensorrt,_retinanet,_cuda,_batch_size.2,_v4.1-dev_) --> detect,os detect-cpu,586c8a43320142f7 --> detect,os - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_calibrate,_retinanet,_cuda,_tensorrt,_batch_size.2,_v4.1-dev_) --> detect,cpu - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_calibrate,_retinanet,_cuda,_tensorrt,_batch_size.2,_v4.1-dev_) --> get,sys-utils-cm - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_calibrate,_retinanet,_cuda,_tensorrt,_batch_size.2,_v4.1-dev_) --> get,mlperf,inference,nvidia,scratch,space,_version.4_0 + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_calibrate,_tensorrt,_retinanet,_cuda,_batch_size.2,_v4.1-dev_) --> detect,cpu + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_calibrate,_tensorrt,_retinanet,_cuda,_batch_size.2,_v4.1-dev_) --> get,sys-utils-cm + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_calibrate,_tensorrt,_retinanet,_cuda,_batch_size.2,_v4.1-dev_) --> get,mlperf,inference,nvidia,scratch,space,_version.4_0 get-generic-python-lib,94b62a682bc44791_(_mlperf_logging_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_calibrate,_retinanet,_cuda,_tensorrt,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_mlperf_logging - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_calibrate,_retinanet,_cuda,_tensorrt,_batch_size.2,_v4.1-dev_) --> get,dataset,original,openimages,_validation,_full,_custom-annotations - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_calibrate,_retinanet,_cuda,_tensorrt,_batch_size.2,_v4.1-dev_) --> get,dataset,original,openimages,_calibration - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_calibrate,_retinanet,_cuda,_tensorrt,_batch_size.2,_v4.1-dev_) --> get,mlcommons,inference,src - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_calibrate,_retinanet,_cuda,_tensorrt,_batch_size.2,_v4.1-dev_) --> get,nvidia,mlperf,inference,common-code,_mlcommons + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_calibrate,_tensorrt,_retinanet,_cuda,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_mlperf_logging + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_calibrate,_tensorrt,_retinanet,_cuda,_batch_size.2,_v4.1-dev_) --> get,dataset,original,openimages,_validation,_full,_custom-annotations + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_calibrate,_tensorrt,_retinanet,_cuda,_batch_size.2,_v4.1-dev_) --> get,dataset,original,openimages,_calibration + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_calibrate,_tensorrt,_retinanet,_cuda,_batch_size.2,_v4.1-dev_) --> get,mlcommons,inference,src + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_calibrate,_tensorrt,_retinanet,_cuda,_batch_size.2,_v4.1-dev_) --> get,nvidia,mlperf,inference,common-code,_mlcommons pull-git-repo,c23132ed65c4421d --> detect,os - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_calibrate,_retinanet,_cuda,_tensorrt,_batch_size.2,_v4.1-dev_) --> pull,git,repo + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_calibrate,_tensorrt,_retinanet,_cuda,_batch_size.2,_v4.1-dev_) --> pull,git,repo get-generic-python-lib,94b62a682bc44791_(_package.pycuda_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_calibrate,_retinanet,_cuda,_tensorrt,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_package.pycuda - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_calibrate,_retinanet,_cuda,_tensorrt,_batch_size.2,_v4.1-dev_) --> get,nvidia,mitten - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_calibrate,_retinanet,_cuda,_tensorrt,_batch_size.2,_v4.1-dev_) --> reproduce,mlperf,inference,nvidia,harness,_download_model,_retinanet,_cuda,_tensorrt,_v4.1-dev,_num-gpus.1 + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_calibrate,_tensorrt,_retinanet,_cuda,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_package.pycuda + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_calibrate,_tensorrt,_retinanet,_cuda,_batch_size.2,_v4.1-dev_) --> get,nvidia,mitten + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_calibrate,_tensorrt,_retinanet,_cuda,_batch_size.2,_v4.1-dev_) --> reproduce,mlperf,inference,nvidia,harness,_download_model,_tensorrt,_retinanet,_cuda,_v4.1-dev,_num-gpus.1 get-generic-python-lib,94b62a682bc44791_(_Pillow_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_calibrate,_retinanet,_cuda,_tensorrt,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_Pillow + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_calibrate,_tensorrt,_retinanet,_cuda,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_Pillow get-generic-python-lib,94b62a682bc44791_(_opencv-python_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_calibrate,_retinanet,_cuda,_tensorrt,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_opencv-python + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_calibrate,_tensorrt,_retinanet,_cuda,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_opencv-python get-generic-python-lib,94b62a682bc44791_(_numpy_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_calibrate,_retinanet,_cuda,_tensorrt,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_numpy + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_calibrate,_tensorrt,_retinanet,_cuda,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_numpy get-generic-python-lib,94b62a682bc44791_(_pycocotools_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_calibrate,_retinanet,_cuda,_tensorrt,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_pycocotools + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_calibrate,_tensorrt,_retinanet,_cuda,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_pycocotools get-generic-python-lib,94b62a682bc44791_(_onnx-graphsurgeon_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_calibrate,_retinanet,_cuda,_tensorrt,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_onnx-graphsurgeon + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_calibrate,_tensorrt,_retinanet,_cuda,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_onnx-graphsurgeon get-generic-python-lib,94b62a682bc44791_(_package.onnx_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_calibrate,_retinanet,_cuda,_tensorrt,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_package.onnx + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_calibrate,_tensorrt,_retinanet,_cuda,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_package.onnx get-generic-python-lib,94b62a682bc44791_(_package.sympy_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_calibrate,_retinanet,_cuda,_tensorrt,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_package.sympy - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_calibrate,_retinanet,_cuda,_tensorrt,_batch_size.2,_v4.1-dev_) --> save,mlperf,inference,state - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_retinanet,_server,_cuda,_tensorrt,_batch_size.8,_batch_size.2,_v4.1-dev_) --> reproduce,mlperf,inference,nvidia,harness,_calibrate,_retinanet,_cuda,_tensorrt,_batch_size.2,_v4.1-dev + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_calibrate,_tensorrt,_retinanet,_cuda,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_package.sympy + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_calibrate,_tensorrt,_retinanet,_cuda,_batch_size.2,_v4.1-dev_) --> save,mlperf,inference,state + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_server,_retinanet,_cuda,_batch_size.8,_batch_size.2,_v4.1-dev_) --> reproduce,mlperf,inference,nvidia,harness,_calibrate,_tensorrt,_retinanet,_cuda,_batch_size.2,_v4.1-dev get-generic-python-lib,94b62a682bc44791_(_Pillow_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_retinanet,_server,_cuda,_tensorrt,_batch_size.8,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_Pillow + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_server,_retinanet,_cuda,_batch_size.8,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_Pillow get-generic-python-lib,94b62a682bc44791_(_opencv-python_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_retinanet,_server,_cuda,_tensorrt,_batch_size.8,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_opencv-python + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_server,_retinanet,_cuda,_batch_size.8,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_opencv-python get-generic-python-lib,94b62a682bc44791_(_numpy_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_retinanet,_server,_cuda,_tensorrt,_batch_size.8,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_numpy + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_server,_retinanet,_cuda,_batch_size.8,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_numpy get-generic-python-lib,94b62a682bc44791_(_pycocotools_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_retinanet,_server,_cuda,_tensorrt,_batch_size.8,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_pycocotools + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_server,_retinanet,_cuda,_batch_size.8,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_pycocotools get-generic-python-lib,94b62a682bc44791_(_onnx-graphsurgeon_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_retinanet,_server,_cuda,_tensorrt,_batch_size.8,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_onnx-graphsurgeon + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_server,_retinanet,_cuda,_batch_size.8,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_onnx-graphsurgeon get-generic-python-lib,94b62a682bc44791_(_package.onnx_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_retinanet,_server,_cuda,_tensorrt,_batch_size.8,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_package.onnx + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_server,_retinanet,_cuda,_batch_size.8,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_package.onnx get-generic-python-lib,94b62a682bc44791_(_package.sympy_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_retinanet,_server,_cuda,_tensorrt,_batch_size.8,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_package.sympy - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_retinanet,_server,_cuda,_tensorrt,_batch_size.8,_batch_size.2,_v4.1-dev_) --> save,mlperf,inference,state - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_retinanet,_server,_cuda,_tensorrt,_rtx_4090_) --> reproduce,mlperf,inference,nvidia,harness,_build_engine,_retinanet,_server,_cuda,_tensorrt,_batch_size.8,_batch_size.2,_v4.1-dev - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_retinanet,_server,_cuda,_tensorrt,_rtx_4090_) --> reproduce,mlperf,inference,nvidia,harness,_preprocess_data,_retinanet,_cuda,_tensorrt,_batch_size.2,_v4.1-dev + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_server,_retinanet,_cuda,_batch_size.8,_batch_size.2,_v4.1-dev_) --> get,generic-python-lib,_package.sympy + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_server,_retinanet,_cuda,_batch_size.8,_batch_size.2,_v4.1-dev_) --> save,mlperf,inference,state + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_server,_retinanet,_cuda,_rtx_4090_) --> reproduce,mlperf,inference,nvidia,harness,_build_engine,_tensorrt,_server,_retinanet,_cuda,_batch_size.8,_batch_size.2,_v4.1-dev + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_server,_retinanet,_cuda,_rtx_4090_) --> reproduce,mlperf,inference,nvidia,harness,_preprocess_data,_tensorrt,_retinanet,_cuda,_batch_size.2,_v4.1-dev get-generic-python-lib,94b62a682bc44791_(_Pillow_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_retinanet,_server,_cuda,_tensorrt,_rtx_4090_) --> get,generic-python-lib,_Pillow + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_server,_retinanet,_cuda,_rtx_4090_) --> get,generic-python-lib,_Pillow get-generic-python-lib,94b62a682bc44791_(_opencv-python_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_retinanet,_server,_cuda,_tensorrt,_rtx_4090_) --> get,generic-python-lib,_opencv-python + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_server,_retinanet,_cuda,_rtx_4090_) --> get,generic-python-lib,_opencv-python get-generic-python-lib,94b62a682bc44791_(_numpy_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_retinanet,_server,_cuda,_tensorrt,_rtx_4090_) --> get,generic-python-lib,_numpy + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_server,_retinanet,_cuda,_rtx_4090_) --> get,generic-python-lib,_numpy get-generic-python-lib,94b62a682bc44791_(_pycocotools_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_retinanet,_server,_cuda,_tensorrt,_rtx_4090_) --> get,generic-python-lib,_pycocotools + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_server,_retinanet,_cuda,_rtx_4090_) --> get,generic-python-lib,_pycocotools get-generic-python-lib,94b62a682bc44791_(_onnx-graphsurgeon_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_retinanet,_server,_cuda,_tensorrt,_rtx_4090_) --> get,generic-python-lib,_onnx-graphsurgeon + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_server,_retinanet,_cuda,_rtx_4090_) --> get,generic-python-lib,_onnx-graphsurgeon get-generic-python-lib,94b62a682bc44791_(_package.onnx_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_retinanet,_server,_cuda,_tensorrt,_rtx_4090_) --> get,generic-python-lib,_package.onnx + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_server,_retinanet,_cuda,_rtx_4090_) --> get,generic-python-lib,_package.onnx get-generic-python-lib,94b62a682bc44791_(_package.sympy_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_retinanet,_server,_cuda,_tensorrt,_rtx_4090_) --> get,generic-python-lib,_package.sympy + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_server,_retinanet,_cuda,_rtx_4090_) --> get,generic-python-lib,_package.sympy detect-cpu,586c8a43320142f7 --> detect,os benchmark-program,19f369ef47084895 --> detect,cpu benchmark-program-mlperf,cfff0132a8aa4018 --> benchmark-program,program - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_retinanet,_server,_cuda,_tensorrt,_rtx_4090_) --> benchmark-mlperf \ No newline at end of file + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_server,_retinanet,_cuda,_rtx_4090_) --> benchmark-mlperf \ No newline at end of file diff --git a/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/server/cm-deps.png b/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/server/cm-deps.png index aae06f4d..40df5f98 100644 Binary files a/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/server/cm-deps.png and b/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/server/cm-deps.png differ diff --git a/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/server/cm-version-info.json b/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/server/cm-version-info.json index ab54bf50..6a2980dd 100644 --- a/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/server/cm-version-info.json +++ b/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/server/cm-version-info.json @@ -157,7 +157,7 @@ "script_tags": "detect-os,detect,os,info", "script_variations": "", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_retinanet,_server,_cuda,_tensorrt,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_server,_retinanet,_cuda,_rtx_4090 )" } }, { @@ -177,7 +177,7 @@ "script_tags": "detect,cpu,detect-cpu,info", "script_variations": "", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_retinanet,_server,_cuda,_tensorrt,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_server,_retinanet,_cuda,_rtx_4090 )" } }, { @@ -187,7 +187,7 @@ "script_tags": "get,sys-utils-cm", "script_variations": "", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_retinanet,_server,_cuda,_tensorrt,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_server,_retinanet,_cuda,_rtx_4090 )" } }, { @@ -197,7 +197,7 @@ "script_tags": "get,mlperf,inference,nvidia,scratch,space", "script_variations": "", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_retinanet,_server,_cuda,_tensorrt,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_server,_retinanet,_cuda,_rtx_4090 )" } }, { @@ -217,7 +217,7 @@ "script_tags": "get,install,generic,pip-package,generic-python-lib", "script_variations": "mlperf_logging", "version": "4.1.1", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_retinanet,_server,_cuda,_tensorrt,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_server,_retinanet,_cuda,_rtx_4090 )" } }, { @@ -227,7 +227,7 @@ "script_tags": "get,dataset,openimages,open-images,object-detection,original", "script_variations": "validation,full,custom-annotations", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_retinanet,_server,_cuda,_tensorrt,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_server,_retinanet,_cuda,_rtx_4090 )" } }, { @@ -237,7 +237,7 @@ "script_tags": "get,dataset,openimages,open-images,object-detection,original", "script_variations": "calibration", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_retinanet,_server,_cuda,_tensorrt,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_server,_retinanet,_cuda,_rtx_4090 )" } }, { @@ -247,7 +247,7 @@ "script_tags": 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build_engine,_retinanet,_server,_cuda,_tensorrt,_batch_size.8,_batch_size.2,_v4.1-dev )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( build_engine,_tensorrt,_server,_retinanet,_cuda,_batch_size.8,_batch_size.2,_v4.1-dev )" } }, { @@ -1677,7 +1677,7 @@ "script_tags": "get,install,generic,pip-package,generic-python-lib", "script_variations": "pycocotools", "version": "2.0.7", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( build_engine,_retinanet,_server,_cuda,_tensorrt,_batch_size.8,_batch_size.2,_v4.1-dev )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( build_engine,_tensorrt,_server,_retinanet,_cuda,_batch_size.8,_batch_size.2,_v4.1-dev )" } }, { @@ -1697,7 +1697,7 @@ "script_tags": "get,install,generic,pip-package,generic-python-lib", "script_variations": "onnx-graphsurgeon", "version": "0.3.27", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( build_engine,_retinanet,_server,_cuda,_tensorrt,_batch_size.8,_batch_size.2,_v4.1-dev )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( build_engine,_tensorrt,_server,_retinanet,_cuda,_batch_size.8,_batch_size.2,_v4.1-dev )" } }, { @@ -1717,7 +1717,7 @@ "script_tags": "get,install,generic,pip-package,generic-python-lib", "script_variations": "package.onnx", "version": "1.14.1", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( build_engine,_retinanet,_server,_cuda,_tensorrt,_batch_size.8,_batch_size.2,_v4.1-dev )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( build_engine,_tensorrt,_server,_retinanet,_cuda,_batch_size.8,_batch_size.2,_v4.1-dev )" } }, { @@ -1737,7 +1737,7 @@ "script_tags": "get,install,generic,pip-package,generic-python-lib", "script_variations": "package.sympy", "version": "1.13.3", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( build_engine,_retinanet,_server,_cuda,_tensorrt,_batch_size.8,_batch_size.2,_v4.1-dev )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( build_engine,_tensorrt,_server,_retinanet,_cuda,_batch_size.8,_batch_size.2,_v4.1-dev )" } }, { @@ -1747,27 +1747,27 @@ "script_tags": "save,mlperf,inference,implementation,state", "script_variations": "", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( build_engine,_retinanet,_server,_cuda,_tensorrt,_batch_size.8,_batch_size.2,_v4.1-dev )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( build_engine,_tensorrt,_server,_retinanet,_cuda,_batch_size.8,_batch_size.2,_v4.1-dev )" } }, { - "reproduce,mlperf,inference,nvidia,harness,_build_engine,_retinanet,_server,_cuda,_tensorrt,_batch_size.8,_batch_size.2,_v4.1-dev": { + "reproduce,mlperf,inference,nvidia,harness,_build_engine,_tensorrt,_server,_retinanet,_cuda,_batch_size.8,_batch_size.2,_v4.1-dev": { "script_uid": "bc3b17fb430f4732", "script_alias": "app-mlperf-inference-nvidia", "script_tags": "reproduce,mlcommons,mlperf,inference,harness,nvidia-harness,nvidia", - "script_variations": "build_engine,retinanet,server,cuda,tensorrt,batch_size.8,batch_size.2,v4.1-dev", + "script_variations": "build_engine,tensorrt,server,retinanet,cuda,batch_size.8,batch_size.2,v4.1-dev", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_retinanet,_server,_cuda,_tensorrt,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_server,_retinanet,_cuda,_rtx_4090 )" } }, { - "reproduce,mlperf,inference,nvidia,harness,_preprocess_data,_retinanet,_cuda,_tensorrt,_batch_size.2,_v4.1-dev": { + "reproduce,mlperf,inference,nvidia,harness,_preprocess_data,_tensorrt,_retinanet,_cuda,_batch_size.2,_v4.1-dev": { "script_uid": "bc3b17fb430f4732", "script_alias": "app-mlperf-inference-nvidia", "script_tags": "reproduce,mlcommons,mlperf,inference,harness,nvidia-harness,nvidia", - "script_variations": "preprocess_data,retinanet,cuda,tensorrt,batch_size.2,v4.1-dev", + "script_variations": "preprocess_data,tensorrt,retinanet,cuda,batch_size.2,v4.1-dev", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_retinanet,_server,_cuda,_tensorrt,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_server,_retinanet,_cuda,_rtx_4090 )" } }, { @@ -1787,7 +1787,7 @@ "script_tags": "get,install,generic,pip-package,generic-python-lib", "script_variations": "Pillow", "version": "10.4.0", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_retinanet,_server,_cuda,_tensorrt,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_server,_retinanet,_cuda,_rtx_4090 )" } }, { @@ -1807,7 +1807,7 @@ "script_tags": "get,install,generic,pip-package,generic-python-lib", "script_variations": "opencv-python", "version": "4.10.0.84", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_retinanet,_server,_cuda,_tensorrt,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_server,_retinanet,_cuda,_rtx_4090 )" } }, { @@ -1827,7 +1827,7 @@ "script_tags": "get,install,generic,pip-package,generic-python-lib", "script_variations": "numpy", "version": "1.23.5", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_retinanet,_server,_cuda,_tensorrt,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_server,_retinanet,_cuda,_rtx_4090 )" } }, { @@ -1847,7 +1847,7 @@ "script_tags": "get,install,generic,pip-package,generic-python-lib", "script_variations": "pycocotools", "version": "2.0.7", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_retinanet,_server,_cuda,_tensorrt,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_server,_retinanet,_cuda,_rtx_4090 )" } }, { @@ -1867,7 +1867,7 @@ "script_tags": "get,install,generic,pip-package,generic-python-lib", "script_variations": "onnx-graphsurgeon", "version": "0.3.27", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_retinanet,_server,_cuda,_tensorrt,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_server,_retinanet,_cuda,_rtx_4090 )" } }, { @@ -1887,7 +1887,7 @@ "script_tags": "get,install,generic,pip-package,generic-python-lib", "script_variations": "package.onnx", "version": "1.14.1", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_retinanet,_server,_cuda,_tensorrt,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_server,_retinanet,_cuda,_rtx_4090 )" } }, { @@ -1907,7 +1907,7 @@ "script_tags": "get,install,generic,pip-package,generic-python-lib", "script_variations": "package.sympy", "version": "1.13.3", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_retinanet,_server,_cuda,_tensorrt,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_server,_retinanet,_cuda,_rtx_4090 )" } }, { @@ -1947,7 +1947,7 @@ "script_tags": "mlperf,benchmark-mlperf", "script_variations": "", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_retinanet,_server,_cuda,_tensorrt,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_server,_retinanet,_cuda,_rtx_4090 )" } } ] diff --git a/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/server/os_info.json b/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/server/os_info.json index 1267c343..cca704f3 100644 --- a/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/server/os_info.json +++ b/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/server/os_info.json @@ -26,5 +26,5 @@ ], "CM_HOST_PLATFORM_FLAVOR": "x86_64", "CM_HOST_PYTHON_BITS": "64", - "CM_HOST_SYSTEM_NAME": "e891b1c381b6" + "CM_HOST_SYSTEM_NAME": "f77641321894" } \ No newline at end of file diff --git a/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/server/performance_console.out b/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/server/performance_console.out index 60771f15..8114a5f6 100644 --- a/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/server/performance_console.out +++ b/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/server/performance_console.out @@ -1,9 +1,9 @@ -[2024-12-23 03:00:47,510 main.py:229 INFO] Detected system ID: KnownSystem.RTX4090x2 -[2024-12-23 03:00:47,606 harness.py:249 INFO] The harness will load 2 plugins: ['build/plugins/NMSOptPlugin/libnmsoptplugin.so', 'build/plugins/retinanetConcatPlugin/libretinanetconcatplugin.so'] -[2024-12-23 03:00:47,607 generate_conf_files.py:107 INFO] Generated measurements/ entries for RTX4090x2_TRT/retinanet/Server -[2024-12-23 03:00:47,607 harness.py:326 INFO] Updated LD_PRELOAD: /usr/lib/x86_64-linux-gnu/libjemalloc.so.2 -[2024-12-23 03:00:47,607 __init__.py:46 INFO] Running command: ./build/bin/harness_default --plugins="build/plugins/NMSOptPlugin/libnmsoptplugin.so,build/plugins/retinanetConcatPlugin/libretinanetconcatplugin.so" --logfile_outdir="/cm-mount/home/arjun/gh_action_results/valid_results/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/server/performance/run_1" --logfile_prefix="mlperf_log_" --performance_sample_count=64 --test_mode="PerformanceOnly" --gpu_copy_streams=2 --gpu_inference_streams=2 --use_cuda_thread_per_device=true --use_deque_limit=true --gpu_batch_size=8 --map_path="data_maps/open-images-v6-mlperf/val_map.txt" --mlperf_conf_path="/home/cmuser/CM/repos/local/cache/5860c00d55d14786/inference/mlperf.conf" --tensor_path="build/preprocessed_data/open-images-v6-mlperf/validation/Retinanet/int8_linear" --use_graphs=false --user_conf_path="/home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/06b8621fdac54f919c81ba7069bd3a8f.conf" --gpu_engines="./build/engines/RTX4090x2/retinanet/Server/retinanet-Server-gpu-b8-int8.lwis_k_99_MaxP.plan" --max_dlas=0 --scenario Server --model retinanet --response_postprocess openimageeffnms -[2024-12-23 03:00:47,607 __init__.py:53 INFO] Overriding Environment +[2024-12-25 02:05:16,664 main.py:229 INFO] Detected system ID: KnownSystem.RTX4090x2 +[2024-12-25 02:05:16,761 harness.py:249 INFO] The harness will load 2 plugins: ['build/plugins/NMSOptPlugin/libnmsoptplugin.so', 'build/plugins/retinanetConcatPlugin/libretinanetconcatplugin.so'] +[2024-12-25 02:05:16,761 generate_conf_files.py:107 INFO] Generated measurements/ entries for RTX4090x2_TRT/retinanet/Server +[2024-12-25 02:05:16,761 harness.py:326 INFO] Updated LD_PRELOAD: /usr/lib/x86_64-linux-gnu/libjemalloc.so.2 +[2024-12-25 02:05:16,762 __init__.py:46 INFO] Running command: ./build/bin/harness_default --plugins="build/plugins/NMSOptPlugin/libnmsoptplugin.so,build/plugins/retinanetConcatPlugin/libretinanetconcatplugin.so" --logfile_outdir="/cm-mount/home/arjun/gh_action_results/valid_results/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/server/performance/run_1" --logfile_prefix="mlperf_log_" --performance_sample_count=64 --test_mode="PerformanceOnly" --gpu_copy_streams=2 --gpu_inference_streams=2 --use_cuda_thread_per_device=true --use_deque_limit=true --gpu_batch_size=8 --map_path="data_maps/open-images-v6-mlperf/val_map.txt" --mlperf_conf_path="/home/cmuser/CM/repos/local/cache/5860c00d55d14786/inference/mlperf.conf" --tensor_path="build/preprocessed_data/open-images-v6-mlperf/validation/Retinanet/int8_linear" --use_graphs=false --user_conf_path="/home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/cd4a2cf7366748fc9a7ef611a1515594.conf" --gpu_engines="./build/engines/RTX4090x2/retinanet/Server/retinanet-Server-gpu-b8-int8.lwis_k_99_MaxP.plan" --max_dlas=0 --scenario Server --model retinanet --response_postprocess openimageeffnms +[2024-12-25 02:05:16,762 __init__.py:53 INFO] Overriding Environment ERROR: ld.so: object '/usr/lib/x86_64-linux-gnu/libjemalloc.so.2' from LD_PRELOAD cannot be preloaded (cannot open shared object file): ignored. ERROR: ld.so: object '/usr/lib/x86_64-linux-gnu/libjemalloc.so.2' from LD_PRELOAD cannot be preloaded (cannot open shared object file): ignored. benchmark : Benchmark.Retinanet @@ -14,7 +14,7 @@ gpu_copy_streams : 2 gpu_inference_streams : 2 input_dtype : int8 input_format : linear -log_dir : /home/cmuser/CM/repos/local/cache/94a57f78972843c6/repo/closed/NVIDIA/build/logs/2024.12.23-03.00.46 +log_dir : /home/cmuser/CM/repos/local/cache/94a57f78972843c6/repo/closed/NVIDIA/build/logs/2024.12.25-02.05.15 map_path : data_maps/open-images-v6-mlperf/val_map.txt mlperf_conf_path : /home/cmuser/CM/repos/local/cache/5860c00d55d14786/inference/mlperf.conf precision : int8 @@ -28,7 +28,7 @@ test_mode : PerformanceOnly use_cuda_thread_per_device : True use_deque_limit : True use_graphs : False -user_conf_path : /home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/06b8621fdac54f919c81ba7069bd3a8f.conf +user_conf_path : /home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/cd4a2cf7366748fc9a7ef611a1515594.conf system_id : RTX4090x2 config_name : RTX4090x2_retinanet_Server workload_setting : WorkloadSetting(HarnessType.LWIS, AccuracyTarget.k_99, PowerSetting.MaxP) @@ -42,34 +42,34 @@ power_limit : None cpu_freq : None &&&& RUNNING Default_Harness # ./build/bin/harness_default [I] mlperf.conf path: /home/cmuser/CM/repos/local/cache/5860c00d55d14786/inference/mlperf.conf -[I] user.conf path: /home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/06b8621fdac54f919c81ba7069bd3a8f.conf +[I] user.conf path: /home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/cd4a2cf7366748fc9a7ef611a1515594.conf Creating QSL. Finished Creating QSL. Setting up SUT. -[I] [TRT] Loaded engine size: 74 MiB -[I] [TRT] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +6, GPU +10, now: CPU 128, GPU 883 (MiB) -[I] [TRT] [MemUsageChange] Init cuDNN: CPU +2, GPU +10, now: CPU 130, GPU 893 (MiB) +[I] [TRT] Loaded engine size: 73 MiB +[I] [TRT] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +6, GPU +10, now: CPU 127, GPU 881 (MiB) +[I] [TRT] [MemUsageChange] Init cuDNN: CPU +2, GPU +10, now: CPU 129, GPU 891 (MiB) [I] [TRT] [MemUsageChange] TensorRT-managed allocation in engine deserialization: CPU +0, GPU +68, now: CPU 0, GPU 68 (MiB) [I] Device:0.GPU: [0] ./build/engines/RTX4090x2/retinanet/Server/retinanet-Server-gpu-b8-int8.lwis_k_99_MaxP.plan has been successfully loaded. -[I] [TRT] Loaded engine size: 74 MiB +[I] [TRT] Loaded engine size: 73 MiB [W] [TRT] Using an engine plan file across different models of devices is not recommended and is likely to affect performance or even cause errors. -[I] [TRT] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +7, GPU +10, now: CPU 165, GPU 626 (MiB) -[I] [TRT] [MemUsageChange] Init cuDNN: CPU +1, GPU +10, now: CPU 166, GPU 636 (MiB) +[I] [TRT] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +6, GPU +10, now: CPU 163, GPU 624 (MiB) +[I] [TRT] [MemUsageChange] Init cuDNN: CPU +1, GPU +10, now: CPU 164, GPU 634 (MiB) [I] [TRT] [MemUsageChange] TensorRT-managed allocation in engine deserialization: CPU +1, GPU +69, now: CPU 1, GPU 137 (MiB) [I] Device:1.GPU: [0] ./build/engines/RTX4090x2/retinanet/Server/retinanet-Server-gpu-b8-int8.lwis_k_99_MaxP.plan has been successfully loaded. [E] [TRT] 3: [runtime.cpp::~Runtime::401] Error Code 3: API Usage Error (Parameter check failed at: runtime/rt/runtime.cpp::~Runtime::401, condition: mEngineCounter.use_count() == 1 Destroying a runtime before destroying deserialized engines created by the runtime leads to undefined behavior.) -[I] [TRT] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +0, GPU +8, now: CPU 93, GPU 905 (MiB) -[I] [TRT] [MemUsageChange] Init cuDNN: CPU +0, GPU +8, now: CPU 93, GPU 913 (MiB) +[I] [TRT] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +0, GPU +8, now: CPU 91, GPU 903 (MiB) +[I] [TRT] [MemUsageChange] Init cuDNN: CPU +1, GPU +8, now: CPU 92, GPU 911 (MiB) [I] [TRT] [MemUsageChange] TensorRT-managed allocation in IExecutionContext creation: CPU +0, GPU +6111, now: CPU 1, GPU 6248 (MiB) -[I] [TRT] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +0, GPU +8, now: CPU 94, GPU 7033 (MiB) -[I] [TRT] [MemUsageChange] Init cuDNN: CPU +0, GPU +12, now: CPU 94, GPU 7045 (MiB) +[I] [TRT] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +0, GPU +8, now: CPU 92, GPU 7031 (MiB) +[I] [TRT] [MemUsageChange] Init cuDNN: CPU +1, GPU +12, now: CPU 93, GPU 7043 (MiB) [I] [TRT] Could not set default profile 0 for execution context. Profile index must be set explicitly. [I] [TRT] [MemUsageChange] TensorRT-managed allocation in IExecutionContext creation: CPU +1, GPU +6111, now: CPU 2, GPU 12359 (MiB) -[I] [TRT] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +0, GPU +8, now: CPU 95, GPU 648 (MiB) -[I] [TRT] [MemUsageChange] Init cuDNN: CPU +0, GPU +8, now: CPU 95, GPU 656 (MiB) +[I] [TRT] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +0, GPU +8, now: CPU 94, GPU 646 (MiB) +[I] [TRT] [MemUsageChange] Init cuDNN: CPU +0, GPU +8, now: CPU 94, GPU 654 (MiB) [I] [TRT] [MemUsageChange] TensorRT-managed allocation in IExecutionContext creation: CPU +0, GPU +6111, now: CPU 2, GPU 18470 (MiB) -[I] [TRT] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +0, GPU +8, now: CPU 96, GPU 6776 (MiB) -[I] [TRT] [MemUsageChange] Init cuDNN: CPU +1, GPU +12, now: CPU 97, GPU 6788 (MiB) +[I] [TRT] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +0, GPU +8, now: CPU 95, GPU 6774 (MiB) +[I] [TRT] [MemUsageChange] Init cuDNN: CPU +0, GPU +12, now: CPU 95, GPU 6786 (MiB) [I] [TRT] Could not set default profile 0 for execution context. Profile index must be set explicitly. [I] [TRT] [MemUsageChange] TensorRT-managed allocation in IExecutionContext creation: CPU +1, GPU +6111, now: CPU 3, GPU 24581 (MiB) [I] Creating batcher thread: 0 EnableBatcherThreadPerDevice: false @@ -77,7 +77,7 @@ Setting up SUT. [I] Creating cuda thread: 1 Finished setting up SUT. Starting warmup. Running for a minimum of 5 seconds. -Finished warmup. Ran for 5.15263s. +Finished warmup. Ran for 5.15685s. Starting running actual test. ================================================ MLPerf Results Summary @@ -97,17 +97,17 @@ Early Stopping Result: ================================================ Additional Stats ================================================ -Completed samples per second : 1415.00 +Completed samples per second : 1414.99 -Min latency (ns) : 2791060 -Max latency (ns) : 31466339 -Mean latency (ns) : 13782929 -50.00 percentile latency (ns) : 13537376 -90.00 percentile latency (ns) : 17064287 -95.00 percentile latency (ns) : 18129749 -97.00 percentile latency (ns) : 18822106 -99.00 percentile latency (ns) : 20235023 -99.90 percentile latency (ns) : 23653280 +Min latency (ns) : 2742550 +Max latency (ns) : 31247479 +Mean latency (ns) : 13785689 +50.00 percentile latency (ns) : 13540363 +90.00 percentile latency (ns) : 17065882 +95.00 percentile latency (ns) : 18127387 +97.00 percentile latency (ns) : 18824906 +99.00 percentile latency (ns) : 20222769 +99.90 percentile latency (ns) : 23596887 ================================================ Test Parameters Used @@ -137,30 +137,30 @@ No warnings encountered during test. No errors encountered during test. Finished running actual test. Device Device:0.GPU processed: - 1 batches of size 2 - 18 batches of size 3 - 64 batches of size 4 - 173 batches of size 5 - 355 batches of size 6 - 723 batches of size 7 - 52026 batches of size 8 + 5 batches of size 2 + 17 batches of size 3 + 60 batches of size 4 + 176 batches of size 5 + 343 batches of size 6 + 802 batches of size 7 + 51955 batches of size 8 Memcpy Calls: 0 - PerSampleCudaMemcpy Calls: 424576 + PerSampleCudaMemcpy Calls: 424493 BatchedCudaMemcpy Calls: 0 Device Device:1.GPU processed: 1 batches of size 1 - 5 batches of size 2 - 20 batches of size 3 - 54 batches of size 4 - 163 batches of size 5 - 374 batches of size 6 - 809 batches of size 7 - 51929 batches of size 8 + 1 batches of size 2 + 22 batches of size 3 + 65 batches of size 4 + 161 batches of size 5 + 387 batches of size 6 + 732 batches of size 7 + 51993 batches of size 8 Memcpy Calls: 0 - PerSampleCudaMemcpy Calls: 424440 + PerSampleCudaMemcpy Calls: 424523 BatchedCudaMemcpy Calls: 1 &&&& PASSED Default_Harness # ./build/bin/harness_default -[2024-12-23 03:10:54,260 run_harness.py:166 INFO] Result: result_scheduled_samples_per_sec: 1415.02, Result is VALID +[2024-12-25 02:15:23,417 run_harness.py:166 INFO] Result: result_scheduled_samples_per_sec: 1415.02, Result is VALID ======================== Result summaries: ======================== diff --git a/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/server/system_info.txt b/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/server/system_info.txt index 6366bc14..739a901e 100644 --- a/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/server/system_info.txt +++ b/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/server/system_info.txt @@ -2,10 +2,10 @@ Platform Details ------------------------------------------------------------ 1. uname -a -Linux e891b1c381b6 6.8.0-49-generic #49-Ubuntu SMP PREEMPT_DYNAMIC Mon Nov 4 02:06:24 UTC 2024 x86_64 x86_64 x86_64 GNU/Linux +Linux f77641321894 6.8.0-49-generic #49-Ubuntu SMP PREEMPT_DYNAMIC Mon Nov 4 02:06:24 UTC 2024 x86_64 x86_64 x86_64 GNU/Linux ------------------------------------------------------------ 2. w - 03:10:56 up 12 days, 21:29, 0 users, load average: 0.25, 0.42, 0.66 + 02:15:25 up 14 days, 20:33, 0 users, load average: 0.39, 0.35, 0.60 USER TTY FROM LOGIN@ IDLE JCPU PCPU WHAT ------------------------------------------------------------ 3. Username @@ -40,7 +40,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 4109.764 +cpu MHz : 800.051 cache size : 46080 KB physical id : 0 siblings : 48 @@ -68,7 +68,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 1018.584 +cpu MHz : 800.000 cache size : 46080 KB physical id : 0 siblings : 48 @@ -96,7 +96,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 1668.770 +cpu MHz : 800.000 cache size : 46080 KB physical id : 0 siblings : 48 @@ -152,7 +152,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 800.000 +cpu MHz : 790.854 cache size : 46080 KB physical id : 0 siblings : 48 @@ -404,7 +404,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 1332.363 +cpu MHz : 4300.000 cache size : 46080 KB physical id : 0 siblings : 48 @@ -432,7 +432,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 800.000 +cpu MHz : 3600.000 cache size : 46080 KB physical id : 0 siblings : 48 @@ -460,7 +460,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 800.000 +cpu MHz : 762.186 cache size : 46080 KB physical id : 0 siblings : 48 @@ -516,7 +516,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 1154.283 +cpu MHz : 1102.917 cache size : 46080 KB physical id : 0 siblings : 48 @@ -600,7 +600,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 800.000 +cpu MHz : 4108.471 cache size : 46080 KB physical id : 0 siblings : 48 @@ -628,7 +628,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 800.440 +cpu MHz : 800.000 cache size : 46080 KB physical id : 0 siblings : 48 @@ -684,7 +684,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 3983.700 +cpu MHz : 800.000 cache size : 46080 KB physical id : 0 siblings : 48 @@ -1076,7 +1076,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 4281.779 +cpu MHz : 800.000 cache size : 46080 KB physical id : 0 siblings : 48 @@ -1104,7 +1104,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 800.000 +cpu MHz : 939.395 cache size : 46080 KB physical id : 0 siblings : 48 @@ -1160,7 +1160,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 800.000 +cpu MHz : 4077.294 cache size : 46080 KB physical id : 0 siblings : 48 @@ -1216,7 +1216,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 800.000 +cpu MHz : 798.666 cache size : 46080 KB physical id : 0 siblings : 48 @@ -1244,7 +1244,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 800.000 +cpu MHz : 2313.202 cache size : 46080 KB physical id : 0 siblings : 48 @@ -1328,7 +1328,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 2900.000 +cpu MHz : 800.000 cache size : 46080 KB physical id : 0 siblings : 48 @@ -1356,7 +1356,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 800.000 +cpu MHz : 800.563 cache size : 46080 KB physical id : 0 siblings : 48 @@ -1394,7 +1394,7 @@ CPU family: 6 Model: 143 Model name: Intel(R) Xeon(R) w7-2495X Stepping: 8 -CPU MHz: 3407.674 +CPU MHz: 800.000 CPU max MHz: 4800.0000 CPU min MHz: 800.0000 BogoMIPS: 4992.00 @@ -1424,49 +1424,49 @@ Flags: fpu vme de pse tsc msr pae mce cx8 apic se available: 1 nodes (0) node 0 cpus: 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 node 0 size: 192709 MB -node 0 free: 17928 MB +node 0 free: 14519 MB node distances: node 0 0: 10 ------------------------------------------------------------ 9. /proc/meminfo MemTotal: 197334532 kB -MemFree: 18359228 kB -MemAvailable: 193204916 kB -Buffers: 456344 kB -Cached: 172548824 kB -SwapCached: 46244 kB -Active: 2811928 kB -Inactive: 170623764 kB -Active(anon): 378256 kB -Inactive(anon): 91752 kB -Active(file): 2433672 kB -Inactive(file): 170532012 kB +MemFree: 14868428 kB +MemAvailable: 193019808 kB +Buffers: 663356 kB +Cached: 173823716 kB +SwapCached: 37424 kB +Active: 4869172 kB +Inactive: 170068924 kB +Active(anon): 470748 kB +Inactive(anon): 18528 kB +Active(file): 4398424 kB +Inactive(file): 170050396 kB Unevictable: 3088 kB Mlocked: 0 kB SwapTotal: 8388604 kB -SwapFree: 7975300 kB +SwapFree: 7980272 kB Zswap: 0 kB Zswapped: 0 kB -Dirty: 312 kB +Dirty: 304 kB Writeback: 0 kB -AnonPages: 422788 kB -Mapped: 344576 kB -Shmem: 39480 kB -KReclaimable: 3652300 kB -Slab: 4651648 kB -SReclaimable: 3652300 kB -SUnreclaim: 999348 kB -KernelStack: 17968 kB -PageTables: 21180 kB +AnonPages: 447680 kB +Mapped: 338692 kB +Shmem: 38252 kB +KReclaimable: 5474856 kB +Slab: 6625884 kB +SReclaimable: 5474856 kB +SUnreclaim: 1151028 kB +KernelStack: 18176 kB +PageTables: 21128 kB SecPageTables: 0 kB NFS_Unstable: 0 kB Bounce: 0 kB WritebackTmp: 0 kB CommitLimit: 107055868 kB -Committed_AS: 5413020 kB +Committed_AS: 5501884 kB VmallocTotal: 13743895347199 kB -VmallocUsed: 156408 kB +VmallocUsed: 156532 kB VmallocChunk: 0 kB Percpu: 129600 kB HardwareCorrupted: 0 kB @@ -1482,8 +1482,8 @@ HugePages_Rsvd: 0 HugePages_Surp: 0 Hugepagesize: 2048 kB Hugetlb: 0 kB -DirectMap4k: 45602404 kB -DirectMap2M: 152057856 kB +DirectMap4k: 49014372 kB +DirectMap2M: 148645888 kB DirectMap1G: 5242880 kB ------------------------------------------------------------ 10. who -r @@ -1738,16 +1738,16 @@ dev.tty.ldisc_autoload = 1 dev.tty.legacy_tiocsti = 0 fs.aio-max-nr = 65536 fs.aio-nr = 0 -fs.dentry-state = 1405629 1291830 45 0 686826 0 +fs.dentry-state = 1888296 1741259 45 0 969237 0 fs.dir-notify-enable = 1 fs.epoll.max_user_watches = 43912503 fs.fanotify.max_queued_events = 16384 fs.fanotify.max_user_groups = 128 fs.fanotify.max_user_marks = 1048576 fs.file-max = 9223372036854775807 -fs.file-nr = 6368 0 9223372036854775807 -fs.inode-nr = 786322 176959 -fs.inode-state = 786322 176959 0 0 0 0 0 +fs.file-nr = 6080 0 9223372036854775807 +fs.inode-nr = 1246012 460556 +fs.inode-state = 1246012 460556 0 0 0 0 0 fs.inotify.max_queued_events = 16384 fs.inotify.max_user_instances = 128 fs.inotify.max_user_watches = 65536 @@ -1775,7 +1775,7 @@ fs.quota.drops = 0 fs.quota.free_dquots = 0 fs.quota.lookups = 0 fs.quota.reads = 0 -fs.quota.syncs = 1460 +fs.quota.syncs = 1742 fs.quota.writes = 0 fs.suid_dumpable = 2 fs.verity.require_signatures = 0 @@ -1802,7 +1802,7 @@ kernel.ftrace_dump_on_oops = 0 kernel.ftrace_enabled = 1 kernel.hardlockup_all_cpu_backtrace = 0 kernel.hardlockup_panic = 0 -kernel.hostname = e891b1c381b6 +kernel.hostname = f77641321894 kernel.hotplug = kernel.hung_task_all_cpu_backtrace = 0 kernel.hung_task_check_count = 4194304 @@ -1834,7 +1834,7 @@ kernel.msgmnb = 16384 kernel.msgmni = 32000 kernel.ngroups_max = 65536 kernel.nmi_watchdog = 1 -kernel.ns_last_pid = 33192 +kernel.ns_last_pid = 33197 kernel.numa_balancing = 0 kernel.numa_balancing_promote_rate_limit_MBps = 65536 kernel.oops_all_cpu_backtrace = 0 @@ -1865,13 +1865,13 @@ kernel.printk_devkmsg = on kernel.printk_ratelimit = 5 kernel.printk_ratelimit_burst = 10 kernel.pty.max = 4096 -kernel.pty.nr = 8 +kernel.pty.nr = 9 kernel.pty.reserve = 1024 kernel.random.boot_id = 29685405-01e1-41c8-8cf0-dcaddcc1862c kernel.random.entropy_avail = 256 kernel.random.poolsize = 256 kernel.random.urandom_min_reseed_secs = 60 -kernel.random.uuid = 1a48ce7e-17b9-486b-a984-22944fb0f92d +kernel.random.uuid = 4e6b6085-9639-4ec8-a561-2df5702af27d kernel.random.write_wakeup_threshold = 256 kernel.randomize_va_space = 2 kernel.real-root-dev = 0 diff --git a/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/singlestream/README.md b/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/singlestream/README.md index 1bdf73de..010cab65 100644 --- a/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/singlestream/README.md +++ b/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/singlestream/README.md @@ -19,7 +19,7 @@ pip install -U cmind cm rm cache -f -cm pull repo mlcommons@mlperf-automations --checkout=225220c7d9bb7e66e5b9a1e1ebfc3e0180fbd094 +cm pull repo mlcommons@mlperf-automations --checkout=a90475d2de72bf0622cebe8d5ca8eb8c9d872fbd cm run script \ --tags=app,mlperf,inference,generic,_nvidia,_retinanet,_tensorrt,_cuda,_valid,_r4.1-dev_default,_singlestream \ @@ -126,7 +126,7 @@ Platform: RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config Model Precision: int8 ### Accuracy Results -`mAP`: `37.366`, Required accuracy for closed division `>= 37.1745` +`mAP`: `37.297`, Required accuracy for closed division `>= 37.1745` ### Performance Results -`90th percentile latency (ns)`: `1736348.0` +`90th percentile latency (ns)`: `1735586.0` diff --git a/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/singlestream/accuracy_console.out b/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/singlestream/accuracy_console.out index 565e4bec..de8729ad 100644 --- a/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/singlestream/accuracy_console.out +++ b/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/singlestream/accuracy_console.out @@ -1,8 +1,8 @@ -[2024-12-23 01:30:36,804 main.py:229 INFO] Detected system ID: KnownSystem.RTX4090x2 -[2024-12-23 01:30:36,882 harness.py:249 INFO] The harness will load 2 plugins: ['build/plugins/NMSOptPlugin/libnmsoptplugin.so', 'build/plugins/retinanetConcatPlugin/libretinanetconcatplugin.so'] -[2024-12-23 01:30:36,882 generate_conf_files.py:107 INFO] Generated measurements/ entries for RTX4090x2_TRT/retinanet/SingleStream -[2024-12-23 01:30:36,882 __init__.py:46 INFO] Running command: ./build/bin/harness_default --plugins="build/plugins/NMSOptPlugin/libnmsoptplugin.so,build/plugins/retinanetConcatPlugin/libretinanetconcatplugin.so" --logfile_outdir="/cm-mount/home/arjun/gh_action_results/valid_results/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/singlestream/accuracy" --logfile_prefix="mlperf_log_" --performance_sample_count=64 --test_mode="AccuracyOnly" --gpu_copy_streams=1 --gpu_inference_streams=1 --use_deque_limit=true --gpu_batch_size=1 --map_path="data_maps/open-images-v6-mlperf/val_map.txt" --mlperf_conf_path="/home/cmuser/CM/repos/local/cache/5860c00d55d14786/inference/mlperf.conf" --tensor_path="build/preprocessed_data/open-images-v6-mlperf/validation/Retinanet/int8_linear" --use_graphs=false --user_conf_path="/home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/faab3e6f6ffe4b1eb4725ec905701f17.conf" --gpu_engines="./build/engines/RTX4090x2/retinanet/SingleStream/retinanet-SingleStream-gpu-b1-int8.lwis_k_99_MaxP.plan" --max_dlas=0 --scenario SingleStream --model retinanet --response_postprocess openimageeffnms -[2024-12-23 01:30:36,882 __init__.py:53 INFO] Overriding Environment +[2024-12-25 00:34:46,206 main.py:229 INFO] Detected system ID: KnownSystem.RTX4090x2 +[2024-12-25 00:34:46,282 harness.py:249 INFO] The harness will load 2 plugins: ['build/plugins/NMSOptPlugin/libnmsoptplugin.so', 'build/plugins/retinanetConcatPlugin/libretinanetconcatplugin.so'] +[2024-12-25 00:34:46,283 generate_conf_files.py:107 INFO] Generated measurements/ entries for RTX4090x2_TRT/retinanet/SingleStream +[2024-12-25 00:34:46,283 __init__.py:46 INFO] Running command: ./build/bin/harness_default --plugins="build/plugins/NMSOptPlugin/libnmsoptplugin.so,build/plugins/retinanetConcatPlugin/libretinanetconcatplugin.so" --logfile_outdir="/cm-mount/home/arjun/gh_action_results/valid_results/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/singlestream/accuracy" --logfile_prefix="mlperf_log_" --performance_sample_count=64 --test_mode="AccuracyOnly" --gpu_copy_streams=1 --gpu_inference_streams=1 --use_deque_limit=true --gpu_batch_size=1 --map_path="data_maps/open-images-v6-mlperf/val_map.txt" --mlperf_conf_path="/home/cmuser/CM/repos/local/cache/5860c00d55d14786/inference/mlperf.conf" --tensor_path="build/preprocessed_data/open-images-v6-mlperf/validation/Retinanet/int8_linear" --use_graphs=false --user_conf_path="/home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/9cdabce1f9e4451d8a257431d3d7c2eb.conf" --gpu_engines="./build/engines/RTX4090x2/retinanet/SingleStream/retinanet-SingleStream-gpu-b1-int8.lwis_k_99_MaxP.plan" --max_dlas=0 --scenario SingleStream --model retinanet --response_postprocess openimageeffnms +[2024-12-25 00:34:46,283 __init__.py:53 INFO] Overriding Environment benchmark : Benchmark.Retinanet buffer_manager_thread_count : 0 data_dir : /home/cmuser/CM/repos/local/cache/4db00c74da1e44c8/data @@ -12,7 +12,7 @@ gpu_copy_streams : 1 gpu_inference_streams : 1 input_dtype : int8 input_format : linear -log_dir : /home/cmuser/CM/repos/local/cache/94a57f78972843c6/repo/closed/NVIDIA/build/logs/2024.12.23-01.30.35 +log_dir : /home/cmuser/CM/repos/local/cache/94a57f78972843c6/repo/closed/NVIDIA/build/logs/2024.12.25-00.34.44 map_path : data_maps/open-images-v6-mlperf/val_map.txt mlperf_conf_path : /home/cmuser/CM/repos/local/cache/5860c00d55d14786/inference/mlperf.conf precision : int8 @@ -24,7 +24,7 @@ tensor_path : build/preprocessed_data/open-images-v6-mlperf/validation/Retinanet test_mode : AccuracyOnly use_deque_limit : True use_graphs : False -user_conf_path : /home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/faab3e6f6ffe4b1eb4725ec905701f17.conf +user_conf_path : /home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/9cdabce1f9e4451d8a257431d3d7c2eb.conf system_id : RTX4090x2 config_name : RTX4090x2_retinanet_SingleStream workload_setting : WorkloadSetting(HarnessType.LWIS, AccuracyTarget.k_99, PowerSetting.MaxP) @@ -38,7 +38,7 @@ power_limit : None cpu_freq : None &&&& RUNNING Default_Harness # ./build/bin/harness_default [I] mlperf.conf path: /home/cmuser/CM/repos/local/cache/5860c00d55d14786/inference/mlperf.conf -[I] user.conf path: /home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/faab3e6f6ffe4b1eb4725ec905701f17.conf +[I] user.conf path: /home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/9cdabce1f9e4451d8a257431d3d7c2eb.conf Creating QSL. Finished Creating QSL. Setting up SUT. @@ -49,21 +49,21 @@ Setting up SUT. [I] Device:0.GPU: [0] ./build/engines/RTX4090x2/retinanet/SingleStream/retinanet-SingleStream-gpu-b1-int8.lwis_k_99_MaxP.plan has been successfully loaded. [I] [TRT] Loaded engine size: 72 MiB [W] [TRT] Using an engine plan file across different models of devices is not recommended and is likely to affect performance or even cause errors. -[I] [TRT] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +6, GPU +10, now: CPU 158, GPU 625 (MiB) -[I] [TRT] [MemUsageChange] Init cuDNN: CPU +2, GPU +10, now: CPU 160, GPU 635 (MiB) +[I] [TRT] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +6, GPU +10, now: CPU 158, GPU 624 (MiB) +[I] [TRT] [MemUsageChange] Init cuDNN: CPU +1, GPU +10, now: CPU 159, GPU 634 (MiB) [I] [TRT] [MemUsageChange] TensorRT-managed allocation in engine deserialization: CPU +0, GPU +69, now: CPU 0, GPU 137 (MiB) [I] Device:1.GPU: [0] ./build/engines/RTX4090x2/retinanet/SingleStream/retinanet-SingleStream-gpu-b1-int8.lwis_k_99_MaxP.plan has been successfully loaded. [E] [TRT] 3: [runtime.cpp::~Runtime::401] Error Code 3: API Usage Error (Parameter check failed at: runtime/rt/runtime.cpp::~Runtime::401, condition: mEngineCounter.use_count() == 1 Destroying a runtime before destroying deserialized engines created by the runtime leads to undefined behavior.) [I] [TRT] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +0, GPU +8, now: CPU 87, GPU 893 (MiB) [I] [TRT] [MemUsageChange] Init cuDNN: CPU +0, GPU +8, now: CPU 87, GPU 901 (MiB) [I] [TRT] [MemUsageChange] TensorRT-managed allocation in IExecutionContext creation: CPU +1, GPU +764, now: CPU 1, GPU 901 (MiB) -[I] [TRT] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +0, GPU +8, now: CPU 88, GPU 637 (MiB) -[I] [TRT] [MemUsageChange] Init cuDNN: CPU +0, GPU +8, now: CPU 88, GPU 645 (MiB) +[I] [TRT] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +0, GPU +8, now: CPU 88, GPU 636 (MiB) +[I] [TRT] [MemUsageChange] Init cuDNN: CPU +0, GPU +8, now: CPU 88, GPU 644 (MiB) [I] [TRT] [MemUsageChange] TensorRT-managed allocation in IExecutionContext creation: CPU +0, GPU +764, now: CPU 1, GPU 1665 (MiB) [I] Creating batcher thread: 0 EnableBatcherThreadPerDevice: false Finished setting up SUT. Starting warmup. Running for a minimum of 5 seconds. -Finished warmup. Ran for 5.01205s. +Finished warmup. Ran for 5.01237s. Starting running actual test. No warnings encountered during test. @@ -81,34 +81,34 @@ Device Device:1.GPU processed: PerSampleCudaMemcpy Calls: 0 BatchedCudaMemcpy Calls: 12390 &&&& PASSED Default_Harness # ./build/bin/harness_default -[2024-12-23 01:33:05,753 run_harness.py:166 INFO] Result: Accuracy run detected. -[2024-12-23 01:33:05,753 __init__.py:46 INFO] Running command: python3 /home/cmuser/CM/repos/local/cache/94a57f78972843c6/repo/closed/NVIDIA/build/inference/vision/classification_and_detection/tools/accuracy-openimages.py --mlperf-accuracy-file /cm-mount/home/arjun/gh_action_results/valid_results/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/singlestream/accuracy/mlperf_log_accuracy.json --openimages-dir /home/cmuser/CM/repos/local/cache/4db00c74da1e44c8/preprocessed_data/open-images-v6-mlperf --output-file build/retinanet-results.json +[2024-12-25 00:37:19,179 run_harness.py:166 INFO] Result: Accuracy run detected. +[2024-12-25 00:37:19,179 __init__.py:46 INFO] Running command: python3 /home/cmuser/CM/repos/local/cache/94a57f78972843c6/repo/closed/NVIDIA/build/inference/vision/classification_and_detection/tools/accuracy-openimages.py --mlperf-accuracy-file /cm-mount/home/arjun/gh_action_results/valid_results/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/singlestream/accuracy/mlperf_log_accuracy.json --openimages-dir /home/cmuser/CM/repos/local/cache/4db00c74da1e44c8/preprocessed_data/open-images-v6-mlperf --output-file build/retinanet-results.json loading annotations into memory... -Done (t=0.47s) +Done (t=0.54s) creating index... index created! Loading and preparing results... -DONE (t=18.08s) +DONE (t=18.03s) creating index... index created! Running per image evaluation... Evaluate annotation type *bbox* -DONE (t=134.17s). +DONE (t=134.13s). Accumulating evaluation results... -DONE (t=31.92s). - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.374 - Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.523 - Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.404 +DONE (t=32.47s). + Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.373 + Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.522 + Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.403 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.023 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.125 - Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.413 - Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.420 - Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.599 - Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.628 - Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.082 - Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.343 - Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.678 -mAP=37.366% + Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.412 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.419 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.598 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.627 + Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.083 + Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.344 + Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.677 +mAP=37.297% ======================== Result summaries: ======================== diff --git a/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/singlestream/cm-deps.mmd b/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/singlestream/cm-deps.mmd index b12f3c81..a587544c 100644 --- a/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/singlestream/cm-deps.mmd +++ b/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/singlestream/cm-deps.mmd @@ -20,19 +20,19 @@ graph TD get-generic-python-lib,94b62a682bc44791_(_package.numpy_) --> get,generic-python-lib,_pip get-cuda-devices,7a3ede4d3558427a_(_with-pycuda_) --> get,generic-python-lib,_package.numpy app-mlperf-inference,d775cac873ee4231_(_nvidia,_retinanet,_tensorrt,_cuda,_valid,_r4.1-dev_default,_singlestream_) --> get,cuda-devices,_with-pycuda - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_singlestream,_retinanet,_cuda,_tensorrt,_rtx_4090_) --> detect,os + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_retinanet,_cuda,_tensorrt,_singlestream,_rtx_4090_) --> detect,os detect-cpu,586c8a43320142f7 --> detect,os - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_singlestream,_retinanet,_cuda,_tensorrt,_rtx_4090_) --> detect,cpu - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_singlestream,_retinanet,_cuda,_tensorrt,_rtx_4090_) --> get,sys-utils-cm - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_singlestream,_retinanet,_cuda,_tensorrt,_rtx_4090_) --> get,mlperf,inference,nvidia,scratch,space + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_retinanet,_cuda,_tensorrt,_singlestream,_rtx_4090_) --> detect,cpu + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_retinanet,_cuda,_tensorrt,_singlestream,_rtx_4090_) --> get,sys-utils-cm + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_retinanet,_cuda,_tensorrt,_singlestream,_rtx_4090_) --> get,mlperf,inference,nvidia,scratch,space get-generic-python-lib,94b62a682bc44791_(_mlperf_logging_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_singlestream,_retinanet,_cuda,_tensorrt,_rtx_4090_) --> get,generic-python-lib,_mlperf_logging - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_singlestream,_retinanet,_cuda,_tensorrt,_rtx_4090_) --> get,dataset,original,openimages,_validation,_full,_custom-annotations - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_singlestream,_retinanet,_cuda,_tensorrt,_rtx_4090_) --> get,dataset,original,openimages,_calibration - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_singlestream,_retinanet,_cuda,_tensorrt,_rtx_4090_) --> get,mlcommons,inference,src - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_singlestream,_retinanet,_cuda,_tensorrt,_rtx_4090_) --> get,nvidia,mlperf,inference,common-code,_mlcommons + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_retinanet,_cuda,_tensorrt,_singlestream,_rtx_4090_) --> get,generic-python-lib,_mlperf_logging + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_retinanet,_cuda,_tensorrt,_singlestream,_rtx_4090_) --> get,dataset,original,openimages,_validation,_full,_custom-annotations + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_retinanet,_cuda,_tensorrt,_singlestream,_rtx_4090_) --> get,dataset,original,openimages,_calibration + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_retinanet,_cuda,_tensorrt,_singlestream,_rtx_4090_) --> get,mlcommons,inference,src + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_retinanet,_cuda,_tensorrt,_singlestream,_rtx_4090_) --> get,nvidia,mlperf,inference,common-code,_mlcommons pull-git-repo,c23132ed65c4421d --> detect,os - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_singlestream,_retinanet,_cuda,_tensorrt,_rtx_4090_) --> pull,git,repo + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_retinanet,_cuda,_tensorrt,_singlestream,_rtx_4090_) --> pull,git,repo generate-mlperf-inference-user-conf,3af4475745964b93 --> detect,os detect-cpu,586c8a43320142f7 --> detect,os generate-mlperf-inference-user-conf,3af4475745964b93 --> detect,cpu @@ -40,9 +40,9 @@ graph TD generate-mlperf-inference-user-conf,3af4475745964b93 --> get,mlcommons,inference,src get-mlperf-inference-sut-configs,c2fbf72009e2445b --> get,cache,dir,_name.mlperf-inference-sut-configs generate-mlperf-inference-user-conf,3af4475745964b93 --> get,sut,configs - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_singlestream,_retinanet,_cuda,_tensorrt,_rtx_4090_) --> generate,user-conf,mlperf,inference + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_retinanet,_cuda,_tensorrt,_singlestream,_rtx_4090_) --> generate,user-conf,mlperf,inference get-generic-python-lib,94b62a682bc44791_(_package.pycuda_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_singlestream,_retinanet,_cuda,_tensorrt,_rtx_4090_) --> get,generic-python-lib,_package.pycuda + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_retinanet,_cuda,_tensorrt,_singlestream,_rtx_4090_) --> get,generic-python-lib,_package.pycuda get-nvidia-mitten,1c045f2902374de9 --> detect,os get-nvidia-mitten,1c045f2902374de9 --> get,python3 get-generic-python-lib,94b62a682bc44791_(_pycuda_) --> detect,os @@ -55,9 +55,9 @@ graph TD get-nvidia-mitten,1c045f2902374de9 --> get,generic-python-lib,_pycuda get-git-repo,ed603e7292974f10_(_repo.https://github.com/NVIDIA/mitten_) --> detect,os get-nvidia-mitten,1c045f2902374de9 --> get,git,_repo.https://github.com/NVIDIA/mitten - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_singlestream,_retinanet,_cuda,_tensorrt,_rtx_4090_) --> get,nvidia,mitten - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_singlestream,_retinanet,_cuda,_tensorrt,_rtx_4090_) --> get,cuda,_cudnn - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_singlestream,_retinanet,_cuda,_tensorrt,_rtx_4090_) --> get,tensorrt + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_retinanet,_cuda,_tensorrt,_singlestream,_rtx_4090_) --> get,nvidia,mitten + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_retinanet,_cuda,_tensorrt,_singlestream,_rtx_4090_) --> get,cuda,_cudnn + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_retinanet,_cuda,_tensorrt,_singlestream,_rtx_4090_) --> get,tensorrt build-mlperf-inference-server-nvidia,f37403af5e9f4541_(_mlcommons_) --> detect,os detect-cpu,586c8a43320142f7 --> detect,os build-mlperf-inference-server-nvidia,f37403af5e9f4541_(_mlcommons_) --> detect,cpu @@ -115,26 +115,26 @@ graph TD get-generic-python-lib,94b62a682bc44791_(_pycuda_) --> get,python3 add-custom-nvidia-system,b2e6c46c6e8745a3_(_mlcommons_) --> get,generic-python-lib,_pycuda build-mlperf-inference-server-nvidia,f37403af5e9f4541_(_mlcommons_) --> add,custom,system,nvidia,_mlcommons - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_singlestream,_retinanet,_cuda,_tensorrt,_rtx_4090_) --> build,nvidia,inference,server,_mlcommons - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_singlestream,_retinanet,_cuda,_tensorrt,_batch_size.1,_v4.1-dev_) --> detect,os + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_retinanet,_cuda,_tensorrt,_singlestream,_rtx_4090_) --> build,nvidia,inference,server,_mlcommons + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_retinanet,_cuda,_tensorrt,_singlestream,_batch_size.1,_v4.1-dev_) --> detect,os detect-cpu,586c8a43320142f7 --> detect,os - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_singlestream,_retinanet,_cuda,_tensorrt,_batch_size.1,_v4.1-dev_) --> detect,cpu - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_singlestream,_retinanet,_cuda,_tensorrt,_batch_size.1,_v4.1-dev_) --> get,sys-utils-cm - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_singlestream,_retinanet,_cuda,_tensorrt,_batch_size.1,_v4.1-dev_) --> get,mlperf,inference,nvidia,scratch,space,_version.4_0 + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_retinanet,_cuda,_tensorrt,_singlestream,_batch_size.1,_v4.1-dev_) --> detect,cpu + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_retinanet,_cuda,_tensorrt,_singlestream,_batch_size.1,_v4.1-dev_) --> get,sys-utils-cm + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_retinanet,_cuda,_tensorrt,_singlestream,_batch_size.1,_v4.1-dev_) --> get,mlperf,inference,nvidia,scratch,space,_version.4_0 get-generic-python-lib,94b62a682bc44791_(_mlperf_logging_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_singlestream,_retinanet,_cuda,_tensorrt,_batch_size.1,_v4.1-dev_) --> get,generic-python-lib,_mlperf_logging - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_singlestream,_retinanet,_cuda,_tensorrt,_batch_size.1,_v4.1-dev_) --> get,dataset,original,openimages,_validation,_full,_custom-annotations - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_singlestream,_retinanet,_cuda,_tensorrt,_batch_size.1,_v4.1-dev_) --> get,dataset,original,openimages,_calibration - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_singlestream,_retinanet,_cuda,_tensorrt,_batch_size.1,_v4.1-dev_) --> get,mlcommons,inference,src - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_singlestream,_retinanet,_cuda,_tensorrt,_batch_size.1,_v4.1-dev_) --> get,nvidia,mlperf,inference,common-code,_mlcommons + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_retinanet,_cuda,_tensorrt,_singlestream,_batch_size.1,_v4.1-dev_) --> get,generic-python-lib,_mlperf_logging + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_retinanet,_cuda,_tensorrt,_singlestream,_batch_size.1,_v4.1-dev_) --> get,dataset,original,openimages,_validation,_full,_custom-annotations + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_retinanet,_cuda,_tensorrt,_singlestream,_batch_size.1,_v4.1-dev_) --> get,dataset,original,openimages,_calibration + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_retinanet,_cuda,_tensorrt,_singlestream,_batch_size.1,_v4.1-dev_) --> get,mlcommons,inference,src + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_retinanet,_cuda,_tensorrt,_singlestream,_batch_size.1,_v4.1-dev_) --> get,nvidia,mlperf,inference,common-code,_mlcommons pull-git-repo,c23132ed65c4421d --> detect,os - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_singlestream,_retinanet,_cuda,_tensorrt,_batch_size.1,_v4.1-dev_) --> pull,git,repo + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_retinanet,_cuda,_tensorrt,_singlestream,_batch_size.1,_v4.1-dev_) --> pull,git,repo get-generic-python-lib,94b62a682bc44791_(_package.pycuda_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_singlestream,_retinanet,_cuda,_tensorrt,_batch_size.1,_v4.1-dev_) --> get,generic-python-lib,_package.pycuda - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_singlestream,_retinanet,_cuda,_tensorrt,_batch_size.1,_v4.1-dev_) --> get,nvidia,mitten - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_singlestream,_retinanet,_cuda,_tensorrt,_batch_size.1,_v4.1-dev_) --> get,cuda,_cudnn - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_singlestream,_retinanet,_cuda,_tensorrt,_batch_size.1,_v4.1-dev_) --> get,tensorrt - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_singlestream,_retinanet,_cuda,_tensorrt,_batch_size.1,_v4.1-dev_) --> build,nvidia,inference,server,_mlcommons + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_retinanet,_cuda,_tensorrt,_singlestream,_batch_size.1,_v4.1-dev_) --> get,generic-python-lib,_package.pycuda + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_retinanet,_cuda,_tensorrt,_singlestream,_batch_size.1,_v4.1-dev_) --> get,nvidia,mitten + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_retinanet,_cuda,_tensorrt,_singlestream,_batch_size.1,_v4.1-dev_) --> get,cuda,_cudnn + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_retinanet,_cuda,_tensorrt,_singlestream,_batch_size.1,_v4.1-dev_) --> get,tensorrt + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_retinanet,_cuda,_tensorrt,_singlestream,_batch_size.1,_v4.1-dev_) --> build,nvidia,inference,server,_mlcommons app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_retinanet,_cuda,_tensorrt,_v4.1-dev_) --> detect,os detect-cpu,586c8a43320142f7 --> detect,os app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_retinanet,_cuda,_tensorrt,_v4.1-dev_) --> detect,cpu @@ -191,7 +191,7 @@ graph TD get-generic-python-lib,94b62a682bc44791_(_package.sympy_) --> get,generic-python-lib,_pip app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_retinanet,_cuda,_tensorrt,_v4.1-dev_) --> get,generic-python-lib,_package.sympy app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_retinanet,_cuda,_tensorrt,_v4.1-dev_) --> save,mlperf,inference,state - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_singlestream,_retinanet,_cuda,_tensorrt,_batch_size.1,_v4.1-dev_) --> reproduce,mlperf,inference,nvidia,harness,_preprocess_data,_retinanet,_cuda,_tensorrt,_v4.1-dev + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_retinanet,_cuda,_tensorrt,_singlestream,_batch_size.1,_v4.1-dev_) --> reproduce,mlperf,inference,nvidia,harness,_preprocess_data,_retinanet,_cuda,_tensorrt,_v4.1-dev app-mlperf-inference-nvidia,bc3b17fb430f4732_(_download_model,_retinanet,_cuda,_tensorrt,_v4.1-dev_) --> detect,os detect-cpu,586c8a43320142f7 --> detect,os app-mlperf-inference-nvidia,bc3b17fb430f4732_(_download_model,_retinanet,_cuda,_tensorrt,_v4.1-dev_) --> detect,cpu @@ -231,7 +231,7 @@ graph TD get-generic-python-lib,94b62a682bc44791_(_package.sympy_) --> get,python3 app-mlperf-inference-nvidia,bc3b17fb430f4732_(_download_model,_retinanet,_cuda,_tensorrt,_v4.1-dev_) --> get,generic-python-lib,_package.sympy app-mlperf-inference-nvidia,bc3b17fb430f4732_(_download_model,_retinanet,_cuda,_tensorrt,_v4.1-dev_) --> save,mlperf,inference,state - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_singlestream,_retinanet,_cuda,_tensorrt,_batch_size.1,_v4.1-dev_) --> reproduce,mlperf,inference,nvidia,harness,_download_model,_retinanet,_cuda,_tensorrt,_v4.1-dev + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_retinanet,_cuda,_tensorrt,_singlestream,_batch_size.1,_v4.1-dev_) --> reproduce,mlperf,inference,nvidia,harness,_download_model,_retinanet,_cuda,_tensorrt,_v4.1-dev app-mlperf-inference-nvidia,bc3b17fb430f4732_(_calibrate,_retinanet,_cuda,_tensorrt,_v4.1-dev_) --> detect,os detect-cpu,586c8a43320142f7 --> detect,os app-mlperf-inference-nvidia,bc3b17fb430f4732_(_calibrate,_retinanet,_cuda,_tensorrt,_v4.1-dev_) --> detect,cpu @@ -297,39 +297,39 @@ graph TD get-generic-python-lib,94b62a682bc44791_(_package.sympy_) --> get,python3 app-mlperf-inference-nvidia,bc3b17fb430f4732_(_calibrate,_retinanet,_cuda,_tensorrt,_v4.1-dev_) --> get,generic-python-lib,_package.sympy app-mlperf-inference-nvidia,bc3b17fb430f4732_(_calibrate,_retinanet,_cuda,_tensorrt,_v4.1-dev_) --> save,mlperf,inference,state - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_singlestream,_retinanet,_cuda,_tensorrt,_batch_size.1,_v4.1-dev_) --> reproduce,mlperf,inference,nvidia,harness,_calibrate,_retinanet,_cuda,_tensorrt,_v4.1-dev + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_retinanet,_cuda,_tensorrt,_singlestream,_batch_size.1,_v4.1-dev_) --> reproduce,mlperf,inference,nvidia,harness,_calibrate,_retinanet,_cuda,_tensorrt,_v4.1-dev get-generic-python-lib,94b62a682bc44791_(_Pillow_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_singlestream,_retinanet,_cuda,_tensorrt,_batch_size.1,_v4.1-dev_) --> get,generic-python-lib,_Pillow + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_retinanet,_cuda,_tensorrt,_singlestream,_batch_size.1,_v4.1-dev_) --> get,generic-python-lib,_Pillow get-generic-python-lib,94b62a682bc44791_(_opencv-python_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_singlestream,_retinanet,_cuda,_tensorrt,_batch_size.1,_v4.1-dev_) --> get,generic-python-lib,_opencv-python + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_retinanet,_cuda,_tensorrt,_singlestream,_batch_size.1,_v4.1-dev_) --> get,generic-python-lib,_opencv-python get-generic-python-lib,94b62a682bc44791_(_numpy_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_singlestream,_retinanet,_cuda,_tensorrt,_batch_size.1,_v4.1-dev_) --> get,generic-python-lib,_numpy + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_retinanet,_cuda,_tensorrt,_singlestream,_batch_size.1,_v4.1-dev_) --> get,generic-python-lib,_numpy get-generic-python-lib,94b62a682bc44791_(_pycocotools_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_singlestream,_retinanet,_cuda,_tensorrt,_batch_size.1,_v4.1-dev_) --> get,generic-python-lib,_pycocotools + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_retinanet,_cuda,_tensorrt,_singlestream,_batch_size.1,_v4.1-dev_) --> get,generic-python-lib,_pycocotools get-generic-python-lib,94b62a682bc44791_(_onnx-graphsurgeon_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_singlestream,_retinanet,_cuda,_tensorrt,_batch_size.1,_v4.1-dev_) --> get,generic-python-lib,_onnx-graphsurgeon + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_retinanet,_cuda,_tensorrt,_singlestream,_batch_size.1,_v4.1-dev_) --> get,generic-python-lib,_onnx-graphsurgeon get-generic-python-lib,94b62a682bc44791_(_package.onnx_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_singlestream,_retinanet,_cuda,_tensorrt,_batch_size.1,_v4.1-dev_) --> get,generic-python-lib,_package.onnx + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_retinanet,_cuda,_tensorrt,_singlestream,_batch_size.1,_v4.1-dev_) --> get,generic-python-lib,_package.onnx get-generic-python-lib,94b62a682bc44791_(_package.sympy_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_singlestream,_retinanet,_cuda,_tensorrt,_batch_size.1,_v4.1-dev_) --> get,generic-python-lib,_package.sympy - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_singlestream,_retinanet,_cuda,_tensorrt,_batch_size.1,_v4.1-dev_) --> save,mlperf,inference,state - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_singlestream,_retinanet,_cuda,_tensorrt,_rtx_4090_) --> reproduce,mlperf,inference,nvidia,harness,_build_engine,_singlestream,_retinanet,_cuda,_tensorrt,_batch_size.1,_v4.1-dev - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_singlestream,_retinanet,_cuda,_tensorrt,_rtx_4090_) --> reproduce,mlperf,inference,nvidia,harness,_preprocess_data,_retinanet,_cuda,_tensorrt,_v4.1-dev + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_retinanet,_cuda,_tensorrt,_singlestream,_batch_size.1,_v4.1-dev_) --> get,generic-python-lib,_package.sympy + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_retinanet,_cuda,_tensorrt,_singlestream,_batch_size.1,_v4.1-dev_) --> save,mlperf,inference,state + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_retinanet,_cuda,_tensorrt,_singlestream,_rtx_4090_) --> reproduce,mlperf,inference,nvidia,harness,_build_engine,_retinanet,_cuda,_tensorrt,_singlestream,_batch_size.1,_v4.1-dev + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_retinanet,_cuda,_tensorrt,_singlestream,_rtx_4090_) --> reproduce,mlperf,inference,nvidia,harness,_preprocess_data,_retinanet,_cuda,_tensorrt,_v4.1-dev get-generic-python-lib,94b62a682bc44791_(_Pillow_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_singlestream,_retinanet,_cuda,_tensorrt,_rtx_4090_) --> get,generic-python-lib,_Pillow + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_retinanet,_cuda,_tensorrt,_singlestream,_rtx_4090_) --> get,generic-python-lib,_Pillow get-generic-python-lib,94b62a682bc44791_(_opencv-python_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_singlestream,_retinanet,_cuda,_tensorrt,_rtx_4090_) --> get,generic-python-lib,_opencv-python + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_retinanet,_cuda,_tensorrt,_singlestream,_rtx_4090_) --> get,generic-python-lib,_opencv-python get-generic-python-lib,94b62a682bc44791_(_numpy_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_singlestream,_retinanet,_cuda,_tensorrt,_rtx_4090_) --> get,generic-python-lib,_numpy + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_retinanet,_cuda,_tensorrt,_singlestream,_rtx_4090_) --> get,generic-python-lib,_numpy get-generic-python-lib,94b62a682bc44791_(_pycocotools_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_singlestream,_retinanet,_cuda,_tensorrt,_rtx_4090_) --> get,generic-python-lib,_pycocotools + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_retinanet,_cuda,_tensorrt,_singlestream,_rtx_4090_) --> get,generic-python-lib,_pycocotools get-generic-python-lib,94b62a682bc44791_(_onnx-graphsurgeon_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_singlestream,_retinanet,_cuda,_tensorrt,_rtx_4090_) --> get,generic-python-lib,_onnx-graphsurgeon + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_retinanet,_cuda,_tensorrt,_singlestream,_rtx_4090_) --> get,generic-python-lib,_onnx-graphsurgeon get-generic-python-lib,94b62a682bc44791_(_package.onnx_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_singlestream,_retinanet,_cuda,_tensorrt,_rtx_4090_) --> get,generic-python-lib,_package.onnx + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_retinanet,_cuda,_tensorrt,_singlestream,_rtx_4090_) --> get,generic-python-lib,_package.onnx get-generic-python-lib,94b62a682bc44791_(_package.sympy_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_singlestream,_retinanet,_cuda,_tensorrt,_rtx_4090_) --> get,generic-python-lib,_package.sympy + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_retinanet,_cuda,_tensorrt,_singlestream,_rtx_4090_) --> get,generic-python-lib,_package.sympy detect-cpu,586c8a43320142f7 --> detect,os benchmark-program,19f369ef47084895 --> detect,cpu benchmark-program-mlperf,cfff0132a8aa4018 --> benchmark-program,program - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_singlestream,_retinanet,_cuda,_tensorrt,_rtx_4090_) --> benchmark-mlperf \ No newline at end of file + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_retinanet,_cuda,_tensorrt,_singlestream,_rtx_4090_) --> benchmark-mlperf \ No newline at end of file diff --git a/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/singlestream/cm-deps.png b/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/singlestream/cm-deps.png index 9e28f112..fa979305 100644 Binary files a/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/singlestream/cm-deps.png and b/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/singlestream/cm-deps.png differ diff --git a/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/singlestream/cm-version-info.json b/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/singlestream/cm-version-info.json index 9cc02596..b02ca6f5 100644 --- a/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/singlestream/cm-version-info.json +++ b/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/singlestream/cm-version-info.json @@ -217,7 +217,7 @@ "script_tags": "detect-os,detect,os,info", "script_variations": "", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_singlestream,_retinanet,_cuda,_tensorrt,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_retinanet,_cuda,_tensorrt,_singlestream,_rtx_4090 )" } }, { @@ -237,7 +237,7 @@ "script_tags": "detect,cpu,detect-cpu,info", "script_variations": "", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_singlestream,_retinanet,_cuda,_tensorrt,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_retinanet,_cuda,_tensorrt,_singlestream,_rtx_4090 )" } }, { @@ -247,7 +247,7 @@ "script_tags": "get,sys-utils-cm", "script_variations": "", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_singlestream,_retinanet,_cuda,_tensorrt,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_retinanet,_cuda,_tensorrt,_singlestream,_rtx_4090 )" } }, { @@ -257,7 +257,7 @@ "script_tags": "get,mlperf,inference,nvidia,scratch,space", "script_variations": "", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_singlestream,_retinanet,_cuda,_tensorrt,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_retinanet,_cuda,_tensorrt,_singlestream,_rtx_4090 )" } }, { @@ -277,7 +277,7 @@ "script_tags": "get,install,generic,pip-package,generic-python-lib", "script_variations": "mlperf_logging", "version": "4.1.1", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_singlestream,_retinanet,_cuda,_tensorrt,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_retinanet,_cuda,_tensorrt,_singlestream,_rtx_4090 )" } }, { @@ -287,7 +287,7 @@ "script_tags": "get,dataset,openimages,open-images,object-detection,original", "script_variations": "validation,full,custom-annotations", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_singlestream,_retinanet,_cuda,_tensorrt,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_retinanet,_cuda,_tensorrt,_singlestream,_rtx_4090 )" } }, { @@ -297,7 +297,7 @@ "script_tags": "get,dataset,openimages,open-images,object-detection,original", "script_variations": "calibration", "version": "", - "parent": 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"parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_retinanet,_cuda,_tensorrt,_singlestream,_rtx_4090 )" } }, { @@ -3237,7 +3237,7 @@ "script_tags": "get,install,generic,pip-package,generic-python-lib", "script_variations": "pycocotools", "version": "2.0.7", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_singlestream,_retinanet,_cuda,_tensorrt,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_retinanet,_cuda,_tensorrt,_singlestream,_rtx_4090 )" } }, { @@ -3257,7 +3257,7 @@ "script_tags": "get,install,generic,pip-package,generic-python-lib", "script_variations": "onnx-graphsurgeon", "version": "0.3.27", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_singlestream,_retinanet,_cuda,_tensorrt,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_retinanet,_cuda,_tensorrt,_singlestream,_rtx_4090 )" } }, { @@ -3277,7 +3277,7 @@ "script_tags": "get,install,generic,pip-package,generic-python-lib", "script_variations": "package.onnx", "version": "1.14.1", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_singlestream,_retinanet,_cuda,_tensorrt,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_retinanet,_cuda,_tensorrt,_singlestream,_rtx_4090 )" } }, { @@ -3297,7 +3297,7 @@ "script_tags": "get,install,generic,pip-package,generic-python-lib", "script_variations": "package.sympy", "version": "1.13.3", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_singlestream,_retinanet,_cuda,_tensorrt,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_retinanet,_cuda,_tensorrt,_singlestream,_rtx_4090 )" } }, { @@ -3337,7 +3337,7 @@ "script_tags": "mlperf,benchmark-mlperf", "script_variations": "", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_singlestream,_retinanet,_cuda,_tensorrt,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_retinanet,_cuda,_tensorrt,_singlestream,_rtx_4090 )" } } ] diff --git a/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/singlestream/os_info.json b/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/singlestream/os_info.json index 1267c343..cca704f3 100644 --- a/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/singlestream/os_info.json +++ b/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/singlestream/os_info.json @@ -26,5 +26,5 @@ ], "CM_HOST_PLATFORM_FLAVOR": "x86_64", "CM_HOST_PYTHON_BITS": "64", - "CM_HOST_SYSTEM_NAME": "e891b1c381b6" + "CM_HOST_SYSTEM_NAME": "f77641321894" } \ No newline at end of file diff --git a/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/singlestream/performance_console.out b/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/singlestream/performance_console.out index b83b2337..cdc923f1 100644 --- a/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/singlestream/performance_console.out +++ b/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/singlestream/performance_console.out @@ -1,8 +1,8 @@ -[2024-12-23 01:19:41,956 main.py:229 INFO] Detected system ID: KnownSystem.RTX4090x2 -[2024-12-23 01:19:42,038 harness.py:249 INFO] The harness will load 2 plugins: ['build/plugins/NMSOptPlugin/libnmsoptplugin.so', 'build/plugins/retinanetConcatPlugin/libretinanetconcatplugin.so'] -[2024-12-23 01:19:42,038 generate_conf_files.py:107 INFO] Generated measurements/ entries for RTX4090x2_TRT/retinanet/SingleStream -[2024-12-23 01:19:42,038 __init__.py:46 INFO] Running command: ./build/bin/harness_default --plugins="build/plugins/NMSOptPlugin/libnmsoptplugin.so,build/plugins/retinanetConcatPlugin/libretinanetconcatplugin.so" --logfile_outdir="/cm-mount/home/arjun/gh_action_results/valid_results/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/singlestream/performance/run_1" --logfile_prefix="mlperf_log_" --performance_sample_count=64 --test_mode="PerformanceOnly" --gpu_copy_streams=1 --gpu_inference_streams=1 --use_deque_limit=true --gpu_batch_size=1 --map_path="data_maps/open-images-v6-mlperf/val_map.txt" --mlperf_conf_path="/home/cmuser/CM/repos/local/cache/5860c00d55d14786/inference/mlperf.conf" --tensor_path="build/preprocessed_data/open-images-v6-mlperf/validation/Retinanet/int8_linear" --use_graphs=false --user_conf_path="/home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/8ff01fb5ed9f4474b9592df9cbfefee6.conf" --gpu_engines="./build/engines/RTX4090x2/retinanet/SingleStream/retinanet-SingleStream-gpu-b1-int8.lwis_k_99_MaxP.plan" --max_dlas=0 --scenario SingleStream --model retinanet --response_postprocess openimageeffnms -[2024-12-23 01:19:42,038 __init__.py:53 INFO] Overriding Environment +[2024-12-25 00:23:50,273 main.py:229 INFO] Detected system ID: KnownSystem.RTX4090x2 +[2024-12-25 00:23:50,358 harness.py:249 INFO] The harness will load 2 plugins: ['build/plugins/NMSOptPlugin/libnmsoptplugin.so', 'build/plugins/retinanetConcatPlugin/libretinanetconcatplugin.so'] +[2024-12-25 00:23:50,358 generate_conf_files.py:107 INFO] Generated measurements/ entries for RTX4090x2_TRT/retinanet/SingleStream +[2024-12-25 00:23:50,358 __init__.py:46 INFO] Running command: ./build/bin/harness_default --plugins="build/plugins/NMSOptPlugin/libnmsoptplugin.so,build/plugins/retinanetConcatPlugin/libretinanetconcatplugin.so" --logfile_outdir="/cm-mount/home/arjun/gh_action_results/valid_results/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/singlestream/performance/run_1" --logfile_prefix="mlperf_log_" --performance_sample_count=64 --test_mode="PerformanceOnly" --gpu_copy_streams=1 --gpu_inference_streams=1 --use_deque_limit=true --gpu_batch_size=1 --map_path="data_maps/open-images-v6-mlperf/val_map.txt" --mlperf_conf_path="/home/cmuser/CM/repos/local/cache/5860c00d55d14786/inference/mlperf.conf" --tensor_path="build/preprocessed_data/open-images-v6-mlperf/validation/Retinanet/int8_linear" --use_graphs=false --user_conf_path="/home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/44350ef2918845f2b08961bc0ad1ae94.conf" --gpu_engines="./build/engines/RTX4090x2/retinanet/SingleStream/retinanet-SingleStream-gpu-b1-int8.lwis_k_99_MaxP.plan" --max_dlas=0 --scenario SingleStream --model retinanet --response_postprocess openimageeffnms +[2024-12-25 00:23:50,358 __init__.py:53 INFO] Overriding Environment benchmark : Benchmark.Retinanet buffer_manager_thread_count : 0 data_dir : /home/cmuser/CM/repos/local/cache/4db00c74da1e44c8/data @@ -12,7 +12,7 @@ gpu_copy_streams : 1 gpu_inference_streams : 1 input_dtype : int8 input_format : linear -log_dir : /home/cmuser/CM/repos/local/cache/94a57f78972843c6/repo/closed/NVIDIA/build/logs/2024.12.23-01.19.40 +log_dir : /home/cmuser/CM/repos/local/cache/94a57f78972843c6/repo/closed/NVIDIA/build/logs/2024.12.25-00.23.48 map_path : data_maps/open-images-v6-mlperf/val_map.txt mlperf_conf_path : /home/cmuser/CM/repos/local/cache/5860c00d55d14786/inference/mlperf.conf precision : int8 @@ -24,7 +24,7 @@ tensor_path : build/preprocessed_data/open-images-v6-mlperf/validation/Retinanet test_mode : PerformanceOnly use_deque_limit : True use_graphs : False -user_conf_path : /home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/8ff01fb5ed9f4474b9592df9cbfefee6.conf +user_conf_path : /home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/44350ef2918845f2b08961bc0ad1ae94.conf system_id : RTX4090x2 config_name : RTX4090x2_retinanet_SingleStream workload_setting : WorkloadSetting(HarnessType.LWIS, AccuracyTarget.k_99, PowerSetting.MaxP) @@ -38,7 +38,7 @@ power_limit : None cpu_freq : None &&&& RUNNING Default_Harness # ./build/bin/harness_default [I] mlperf.conf path: /home/cmuser/CM/repos/local/cache/5860c00d55d14786/inference/mlperf.conf -[I] user.conf path: /home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/8ff01fb5ed9f4474b9592df9cbfefee6.conf +[I] user.conf path: /home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/44350ef2918845f2b08961bc0ad1ae94.conf Creating QSL. Finished Creating QSL. Setting up SUT. @@ -50,7 +50,7 @@ Setting up SUT. [I] [TRT] Loaded engine size: 72 MiB [W] [TRT] Using an engine plan file across different models of devices is not recommended and is likely to affect performance or even cause errors. [I] [TRT] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +6, GPU +10, now: CPU 158, GPU 625 (MiB) -[I] [TRT] [MemUsageChange] Init cuDNN: CPU +2, GPU +10, now: CPU 160, GPU 635 (MiB) +[I] [TRT] [MemUsageChange] Init cuDNN: CPU +1, GPU +10, now: CPU 159, GPU 635 (MiB) [I] [TRT] [MemUsageChange] TensorRT-managed allocation in engine deserialization: CPU +0, GPU +69, now: CPU 0, GPU 137 (MiB) [I] Device:1.GPU: [0] ./build/engines/RTX4090x2/retinanet/SingleStream/retinanet-SingleStream-gpu-b1-int8.lwis_k_99_MaxP.plan has been successfully loaded. [E] [TRT] 3: [runtime.cpp::~Runtime::401] Error Code 3: API Usage Error (Parameter check failed at: runtime/rt/runtime.cpp::~Runtime::401, condition: mEngineCounter.use_count() == 1 Destroying a runtime before destroying deserialized engines created by the runtime leads to undefined behavior.) @@ -63,7 +63,7 @@ Setting up SUT. [I] Creating batcher thread: 0 EnableBatcherThreadPerDevice: false Finished setting up SUT. Starting warmup. Running for a minimum of 5 seconds. -Finished warmup. Ran for 5.01186s. +Finished warmup. Ran for 5.01286s. Starting running actual test. ================================================ MLPerf Results Summary @@ -71,32 +71,32 @@ MLPerf Results Summary SUT name : LWIS_Server Scenario : SingleStream Mode : PerformanceOnly -90th percentile latency (ns) : 1735993 +90th percentile latency (ns) : 1735339 Result is : VALID Min duration satisfied : Yes Min queries satisfied : Yes Early stopping satisfied: Yes Early Stopping Result: - * Processed at least 64 queries (350949). - * Would discard 34680 highest latency queries. - * Early stopping 90th percentile estimate: 1736348 - * Early stopping 99th percentile estimate: 1809454 + * Processed at least 64 queries (351200). + * Would discard 34705 highest latency queries. + * Early stopping 90th percentile estimate: 1735586 + * Early stopping 99th percentile estimate: 1807521 ================================================ Additional Stats ================================================ -QPS w/ loadgen overhead : 584.91 -QPS w/o loadgen overhead : 588.72 +QPS w/ loadgen overhead : 585.33 +QPS w/o loadgen overhead : 589.08 -Min latency (ns) : 1629520 -Max latency (ns) : 2213670 -Mean latency (ns) : 1698601 -50.00 percentile latency (ns) : 1691995 -90.00 percentile latency (ns) : 1735993 -95.00 percentile latency (ns) : 1755102 -97.00 percentile latency (ns) : 1775037 -99.00 percentile latency (ns) : 1808927 -99.90 percentile latency (ns) : 1869184 +Min latency (ns) : 1631869 +Max latency (ns) : 2071005 +Mean latency (ns) : 1697554 +50.00 percentile latency (ns) : 1691179 +90.00 percentile latency (ns) : 1735339 +95.00 percentile latency (ns) : 1753792 +97.00 percentile latency (ns) : 1772192 +99.00 percentile latency (ns) : 1806957 +99.90 percentile latency (ns) : 1841780 ================================================ Test Parameters Used @@ -126,17 +126,17 @@ No warnings encountered during test. No errors encountered during test. Finished running actual test. Device Device:0.GPU processed: - 175475 batches of size 1 + 175600 batches of size 1 Memcpy Calls: 0 PerSampleCudaMemcpy Calls: 0 - BatchedCudaMemcpy Calls: 175475 + BatchedCudaMemcpy Calls: 175600 Device Device:1.GPU processed: - 175474 batches of size 1 + 175600 batches of size 1 Memcpy Calls: 0 PerSampleCudaMemcpy Calls: 0 - BatchedCudaMemcpy Calls: 175474 + BatchedCudaMemcpy Calls: 175600 &&&& PASSED Default_Harness # ./build/bin/harness_default -[2024-12-23 01:29:49,826 run_harness.py:166 INFO] Result: result_90.00_percentile_latency_ns: 1735993, Result is VALID +[2024-12-25 00:33:57,935 run_harness.py:166 INFO] Result: result_90.00_percentile_latency_ns: 1735339, Result is VALID ======================== Result summaries: ======================== diff --git a/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/singlestream/system_info.txt b/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/singlestream/system_info.txt index c5e302aa..dc872219 100644 --- a/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/singlestream/system_info.txt +++ b/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/singlestream/system_info.txt @@ -2,10 +2,10 @@ Platform Details ------------------------------------------------------------ 1. uname -a -Linux e891b1c381b6 6.8.0-49-generic #49-Ubuntu SMP PREEMPT_DYNAMIC Mon Nov 4 02:06:24 UTC 2024 x86_64 x86_64 x86_64 GNU/Linux +Linux f77641321894 6.8.0-49-generic #49-Ubuntu SMP PREEMPT_DYNAMIC Mon Nov 4 02:06:24 UTC 2024 x86_64 x86_64 x86_64 GNU/Linux ------------------------------------------------------------ 2. w - 01:30:15 up 12 days, 19:48, 0 users, load average: 0.58, 0.60, 0.91 + 00:34:23 up 14 days, 18:52, 0 users, load average: 0.34, 0.29, 0.48 USER TTY FROM LOGIN@ IDLE JCPU PCPU WHAT ------------------------------------------------------------ 3. Username @@ -40,7 +40,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 3402.599 +cpu MHz : 3388.111 cache size : 46080 KB physical id : 0 siblings : 48 @@ -68,7 +68,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 2800.000 +cpu MHz : 800.172 cache size : 46080 KB physical id : 0 siblings : 48 @@ -96,7 +96,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 800.016 +cpu MHz : 2800.000 cache size : 46080 KB physical id : 0 siblings : 48 @@ -124,7 +124,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 800.000 +cpu MHz : 3968.808 cache size : 46080 KB physical id : 0 siblings : 48 @@ -152,7 +152,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 3927.845 +cpu MHz : 800.000 cache size : 46080 KB physical id : 0 siblings : 48 @@ -180,7 +180,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 799.937 +cpu MHz : 801.092 cache size : 46080 KB physical id : 0 siblings : 48 @@ -404,7 +404,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 1100.000 +cpu MHz : 800.000 cache size : 46080 KB physical id : 0 siblings : 48 @@ -432,7 +432,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 900.397 +cpu MHz : 900.000 cache size : 46080 KB physical id : 0 siblings : 48 @@ -460,7 +460,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 800.000 +cpu MHz : 799.115 cache size : 46080 KB physical id : 0 siblings : 48 @@ -544,7 +544,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 797.255 +cpu MHz : 800.000 cache size : 46080 KB physical id : 0 siblings : 48 @@ -656,7 +656,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 2400.000 +cpu MHz : 800.000 cache size : 46080 KB physical id : 0 siblings : 48 @@ -712,7 +712,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 795.010 +cpu MHz : 800.000 cache size : 46080 KB physical id : 0 siblings : 48 @@ -1076,7 +1076,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 800.000 +cpu MHz : 900.000 cache size : 46080 KB physical id : 0 siblings : 48 @@ -1160,7 +1160,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 800.000 +cpu MHz : 800.111 cache size : 46080 KB physical id : 0 siblings : 48 @@ -1216,7 +1216,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 800.000 +cpu MHz : 799.031 cache size : 46080 KB physical id : 0 siblings : 48 @@ -1272,7 +1272,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 2855.704 +cpu MHz : 800.000 cache size : 46080 KB physical id : 0 siblings : 48 @@ -1300,7 +1300,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 2206.043 +cpu MHz : 3000.000 cache size : 46080 KB physical id : 0 siblings : 48 @@ -1328,7 +1328,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 800.000 +cpu MHz : 1297.773 cache size : 46080 KB physical id : 0 siblings : 48 @@ -1394,7 +1394,7 @@ CPU family: 6 Model: 143 Model name: Intel(R) Xeon(R) w7-2495X Stepping: 8 -CPU MHz: 3096.984 +CPU MHz: 3248.030 CPU max MHz: 4800.0000 CPU min MHz: 800.0000 BogoMIPS: 4992.00 @@ -1424,49 +1424,49 @@ Flags: fpu vme de pse tsc msr pae mce cx8 apic se available: 1 nodes (0) node 0 cpus: 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 node 0 size: 192709 MB -node 0 free: 24313 MB +node 0 free: 27599 MB node distances: node 0 0: 10 ------------------------------------------------------------ 9. /proc/meminfo MemTotal: 197334532 kB -MemFree: 24896604 kB -MemAvailable: 193110444 kB -Buffers: 459344 kB -Cached: 165271428 kB -SwapCached: 46212 kB -Active: 15696036 kB -Inactive: 150453516 kB -Active(anon): 366188 kB -Inactive(anon): 91744 kB -Active(file): 15329848 kB -Inactive(file): 150361772 kB +MemFree: 28260932 kB +MemAvailable: 192869824 kB +Buffers: 697860 kB +Cached: 159984076 kB +SwapCached: 37376 kB +Active: 4376188 kB +Inactive: 156745896 kB +Active(anon): 459544 kB +Inactive(anon): 18536 kB +Active(file): 3916644 kB +Inactive(file): 156727360 kB Unevictable: 3088 kB Mlocked: 0 kB SwapTotal: 8388604 kB -SwapFree: 7974276 kB +SwapFree: 7980272 kB Zswap: 0 kB Zswapped: 0 kB -Dirty: 22636 kB -Writeback: 488 kB -AnonPages: 410964 kB -Mapped: 340200 kB -Shmem: 39148 kB -KReclaimable: 4294516 kB -Slab: 5332420 kB -SReclaimable: 4294516 kB -SUnreclaim: 1037904 kB -KernelStack: 18240 kB -PageTables: 21620 kB +Dirty: 21692 kB +Writeback: 0 kB +AnonPages: 436808 kB +Mapped: 335992 kB +Shmem: 37932 kB +KReclaimable: 5737184 kB +Slab: 6888208 kB +SReclaimable: 5737184 kB +SUnreclaim: 1151024 kB +KernelStack: 18192 kB +PageTables: 21060 kB SecPageTables: 0 kB NFS_Unstable: 0 kB Bounce: 0 kB WritebackTmp: 0 kB CommitLimit: 107055868 kB -Committed_AS: 5399232 kB +Committed_AS: 5486652 kB VmallocTotal: 13743895347199 kB -VmallocUsed: 156468 kB +VmallocUsed: 156548 kB VmallocChunk: 0 kB Percpu: 129600 kB HardwareCorrupted: 0 kB @@ -1482,8 +1482,8 @@ HugePages_Rsvd: 0 HugePages_Surp: 0 Hugepagesize: 2048 kB Hugetlb: 0 kB -DirectMap4k: 45282916 kB -DirectMap2M: 152377344 kB +DirectMap4k: 48948836 kB +DirectMap2M: 148711424 kB DirectMap1G: 5242880 kB ------------------------------------------------------------ 10. who -r @@ -1738,16 +1738,16 @@ dev.tty.ldisc_autoload = 1 dev.tty.legacy_tiocsti = 0 fs.aio-max-nr = 65536 fs.aio-nr = 0 -fs.dentry-state = 1384361 1272111 45 0 670668 0 +fs.dentry-state = 1927497 1802755 45 0 953451 0 fs.dir-notify-enable = 1 fs.epoll.max_user_watches = 43912503 fs.fanotify.max_queued_events = 16384 fs.fanotify.max_user_groups = 128 fs.fanotify.max_user_marks = 1048576 fs.file-max = 9223372036854775807 -fs.file-nr = 6080 0 9223372036854775807 -fs.inode-nr = 781220 176959 -fs.inode-state = 781220 176959 0 0 0 0 0 +fs.file-nr = 5984 0 9223372036854775807 +fs.inode-nr = 1241988 425806 +fs.inode-state = 1241988 425806 0 0 0 0 0 fs.inotify.max_queued_events = 16384 fs.inotify.max_user_instances = 128 fs.inotify.max_user_watches = 65536 @@ -1775,7 +1775,7 @@ fs.quota.drops = 0 fs.quota.free_dquots = 0 fs.quota.lookups = 0 fs.quota.reads = 0 -fs.quota.syncs = 1460 +fs.quota.syncs = 1742 fs.quota.writes = 0 fs.suid_dumpable = 2 fs.verity.require_signatures = 0 @@ -1802,7 +1802,7 @@ kernel.ftrace_dump_on_oops = 0 kernel.ftrace_enabled = 1 kernel.hardlockup_all_cpu_backtrace = 0 kernel.hardlockup_panic = 0 -kernel.hostname = e891b1c381b6 +kernel.hostname = f77641321894 kernel.hotplug = kernel.hung_task_all_cpu_backtrace = 0 kernel.hung_task_check_count = 4194304 @@ -1834,7 +1834,7 @@ kernel.msgmnb = 16384 kernel.msgmni = 32000 kernel.ngroups_max = 65536 kernel.nmi_watchdog = 1 -kernel.ns_last_pid = 13658 +kernel.ns_last_pid = 13661 kernel.numa_balancing = 0 kernel.numa_balancing_promote_rate_limit_MBps = 65536 kernel.oops_all_cpu_backtrace = 0 @@ -1865,13 +1865,13 @@ kernel.printk_devkmsg = on kernel.printk_ratelimit = 5 kernel.printk_ratelimit_burst = 10 kernel.pty.max = 4096 -kernel.pty.nr = 8 +kernel.pty.nr = 9 kernel.pty.reserve = 1024 kernel.random.boot_id = 29685405-01e1-41c8-8cf0-dcaddcc1862c kernel.random.entropy_avail = 256 kernel.random.poolsize = 256 kernel.random.urandom_min_reseed_secs = 60 -kernel.random.uuid = be57925f-75b9-442d-a0e0-03aa9233ab51 +kernel.random.uuid = 8ba61cc3-f54d-4678-abc2-e72cf10ec93e kernel.random.write_wakeup_threshold = 256 kernel.randomize_va_space = 2 kernel.real-root-dev = 0 diff --git a/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/singlestream/user.conf b/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/singlestream/user.conf index d4f3acd4..8883f991 100644 --- a/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/singlestream/user.conf +++ b/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/singlestream/user.conf @@ -1,2 +1,2 @@ -retinanet.SingleStream.target_latency = 0.6794404 +retinanet.SingleStream.target_latency = 0.6790216 retinanet.SingleStream.max_duration = 660000 diff --git a/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/system_info.txt b/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/system_info.txt index 7bb0745b..41a8d4a6 100644 --- a/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/system_info.txt +++ b/open/MLCommons/measurements/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/system_info.txt @@ -2,10 +2,10 @@ Platform Details ------------------------------------------------------------ 1. uname -a -Linux e891b1c381b6 6.8.0-49-generic #49-Ubuntu SMP PREEMPT_DYNAMIC Mon Nov 4 02:06:24 UTC 2024 x86_64 x86_64 x86_64 GNU/Linux +Linux f77641321894 6.8.0-49-generic #49-Ubuntu SMP PREEMPT_DYNAMIC Mon Nov 4 02:06:24 UTC 2024 x86_64 x86_64 x86_64 GNU/Linux ------------------------------------------------------------ 2. w - 02:36:22 up 12 days, 20:54, 0 users, load average: 1.08, 1.12, 1.05 + 01:40:35 up 14 days, 19:58, 0 users, load average: 0.96, 1.04, 1.07 USER TTY FROM LOGIN@ IDLE JCPU PCPU WHAT ------------------------------------------------------------ 3. Username @@ -40,7 +40,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 4300.000 +cpu MHz : 1399.020 cache size : 46080 KB physical id : 0 siblings : 48 @@ -68,7 +68,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 2422.131 +cpu MHz : 800.000 cache size : 46080 KB physical id : 0 siblings : 48 @@ -96,7 +96,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 925.888 +cpu MHz : 800.000 cache size : 46080 KB physical id : 0 siblings : 48 @@ -124,7 +124,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 783.003 +cpu MHz : 800.000 cache size : 46080 KB physical id : 0 siblings : 48 @@ -404,7 +404,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 800.000 +cpu MHz : 4150.900 cache size : 46080 KB physical id : 0 siblings : 48 @@ -460,7 +460,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 972.712 +cpu MHz : 900.000 cache size : 46080 KB physical id : 0 siblings : 48 @@ -488,7 +488,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 3388.395 +cpu MHz : 1102.528 cache size : 46080 KB physical id : 0 siblings : 48 @@ -600,7 +600,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 3066.494 +cpu MHz : 800.000 cache size : 46080 KB physical id : 0 siblings : 48 @@ -656,7 +656,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 4300.000 +cpu MHz : 2700.000 cache size : 46080 KB physical id : 0 siblings : 48 @@ -684,7 +684,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 800.000 +cpu MHz : 4075.303 cache size : 46080 KB physical id : 0 siblings : 48 @@ -740,7 +740,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 800.000 +cpu MHz : 828.934 cache size : 46080 KB physical id : 0 siblings : 48 @@ -768,7 +768,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 851.312 +cpu MHz : 800.000 cache size : 46080 KB physical id : 0 siblings : 48 @@ -852,7 +852,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 800.095 +cpu MHz : 800.298 cache size : 46080 KB physical id : 0 siblings : 48 @@ -1076,7 +1076,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 1100.000 +cpu MHz : 800.000 cache size : 46080 KB physical id : 0 siblings : 48 @@ -1244,7 +1244,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 800.000 +cpu MHz : 1200.000 cache size : 46080 KB physical id : 0 siblings : 48 @@ -1272,7 +1272,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 800.000 +cpu MHz : 3999.556 cache size : 46080 KB physical id : 0 siblings : 48 @@ -1356,7 +1356,7 @@ model : 143 model name : Intel(R) Xeon(R) w7-2495X stepping : 8 microcode : 0x2b0005c0 -cpu MHz : 800.497 +cpu MHz : 800.000 cache size : 46080 KB physical id : 0 siblings : 48 @@ -1394,7 +1394,7 @@ CPU family: 6 Model: 143 Model name: Intel(R) Xeon(R) w7-2495X Stepping: 8 -CPU MHz: 4014.427 +CPU MHz: 4319.196 CPU max MHz: 4800.0000 CPU min MHz: 800.0000 BogoMIPS: 4992.00 @@ -1424,49 +1424,49 @@ Flags: fpu vme de pse tsc msr pae mce cx8 apic se available: 1 nodes (0) node 0 cpus: 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 node 0 size: 192709 MB -node 0 free: 18073 MB +node 0 free: 18344 MB node distances: node 0 0: 10 ------------------------------------------------------------ 9. /proc/meminfo MemTotal: 197334532 kB -MemFree: 18507548 kB -MemAvailable: 193229408 kB -Buffers: 453368 kB -Cached: 172424280 kB -SwapCached: 46224 kB -Active: 2803032 kB -Inactive: 170498804 kB -Active(anon): 371888 kB -Inactive(anon): 91752 kB -Active(file): 2431144 kB -Inactive(file): 170407052 kB +MemFree: 18784616 kB +MemAvailable: 193049204 kB +Buffers: 660160 kB +Cached: 169937564 kB +SwapCached: 37424 kB +Active: 4805056 kB +Inactive: 166242684 kB +Active(anon): 469712 kB +Inactive(anon): 18528 kB +Active(file): 4335344 kB +Inactive(file): 166224156 kB Unevictable: 3088 kB Mlocked: 0 kB SwapTotal: 8388604 kB -SwapFree: 7975300 kB +SwapFree: 7980272 kB Zswap: 0 kB Zswapped: 0 kB -Dirty: 324 kB +Dirty: 232 kB Writeback: 0 kB -AnonPages: 416360 kB -Mapped: 342048 kB -Shmem: 39452 kB -KReclaimable: 3655960 kB -Slab: 4655280 kB -SReclaimable: 3655960 kB -SUnreclaim: 999320 kB -KernelStack: 18016 kB -PageTables: 20964 kB +AnonPages: 446716 kB +Mapped: 337936 kB +Shmem: 38224 kB +KReclaimable: 5477384 kB +Slab: 6629980 kB +SReclaimable: 5477384 kB +SUnreclaim: 1152596 kB +KernelStack: 18304 kB +PageTables: 21524 kB SecPageTables: 0 kB NFS_Unstable: 0 kB Bounce: 0 kB WritebackTmp: 0 kB CommitLimit: 107055868 kB -Committed_AS: 5388516 kB +Committed_AS: 5496848 kB VmallocTotal: 13743895347199 kB -VmallocUsed: 156336 kB +VmallocUsed: 156616 kB VmallocChunk: 0 kB Percpu: 129600 kB HardwareCorrupted: 0 kB @@ -1482,8 +1482,8 @@ HugePages_Rsvd: 0 HugePages_Surp: 0 Hugepagesize: 2048 kB Hugetlb: 0 kB -DirectMap4k: 45491812 kB -DirectMap2M: 152168448 kB +DirectMap4k: 49012324 kB +DirectMap2M: 148647936 kB DirectMap1G: 5242880 kB ------------------------------------------------------------ 10. who -r @@ -1738,16 +1738,16 @@ dev.tty.ldisc_autoload = 1 dev.tty.legacy_tiocsti = 0 fs.aio-max-nr = 65536 fs.aio-nr = 0 -fs.dentry-state = 1399868 1286112 45 0 681183 0 +fs.dentry-state = 1882596 1735623 45 0 963594 0 fs.dir-notify-enable = 1 fs.epoll.max_user_watches = 43912503 fs.fanotify.max_queued_events = 16384 fs.fanotify.max_user_groups = 128 fs.fanotify.max_user_marks = 1048576 fs.file-max = 9223372036854775807 -fs.file-nr = 6080 0 9223372036854775807 -fs.inode-nr = 786206 176959 -fs.inode-state = 786206 176959 0 0 0 0 0 +fs.file-nr = 5888 0 9223372036854775807 +fs.inode-nr = 1245957 460543 +fs.inode-state = 1245957 460543 0 0 0 0 0 fs.inotify.max_queued_events = 16384 fs.inotify.max_user_instances = 128 fs.inotify.max_user_watches = 65536 @@ -1775,7 +1775,7 @@ fs.quota.drops = 0 fs.quota.free_dquots = 0 fs.quota.lookups = 0 fs.quota.reads = 0 -fs.quota.syncs = 1460 +fs.quota.syncs = 1742 fs.quota.writes = 0 fs.suid_dumpable = 2 fs.verity.require_signatures = 0 @@ -1802,7 +1802,7 @@ kernel.ftrace_dump_on_oops = 0 kernel.ftrace_enabled = 1 kernel.hardlockup_all_cpu_backtrace = 0 kernel.hardlockup_panic = 0 -kernel.hostname = e891b1c381b6 +kernel.hostname = f77641321894 kernel.hotplug = kernel.hung_task_all_cpu_backtrace = 0 kernel.hung_task_check_count = 4194304 @@ -1834,7 +1834,7 @@ kernel.msgmnb = 16384 kernel.msgmni = 32000 kernel.ngroups_max = 65536 kernel.nmi_watchdog = 1 -kernel.ns_last_pid = 25849 +kernel.ns_last_pid = 25853 kernel.numa_balancing = 0 kernel.numa_balancing_promote_rate_limit_MBps = 65536 kernel.oops_all_cpu_backtrace = 0 @@ -1865,13 +1865,13 @@ kernel.printk_devkmsg = on kernel.printk_ratelimit = 5 kernel.printk_ratelimit_burst = 10 kernel.pty.max = 4096 -kernel.pty.nr = 8 +kernel.pty.nr = 9 kernel.pty.reserve = 1024 kernel.random.boot_id = 29685405-01e1-41c8-8cf0-dcaddcc1862c kernel.random.entropy_avail = 256 kernel.random.poolsize = 256 kernel.random.urandom_min_reseed_secs = 60 -kernel.random.uuid = c35d2cd6-72ad-46a4-90e8-4b40c5ceb10f +kernel.random.uuid = 781380fa-333f-42e8-9b89-4208eada25cc kernel.random.write_wakeup_threshold = 256 kernel.randomize_va_space = 2 kernel.real-root-dev = 0 diff --git a/open/MLCommons/results/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/multistream/accuracy/accuracy.txt b/open/MLCommons/results/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/multistream/accuracy/accuracy.txt index ca5c1496..d95a3c4e 100644 --- a/open/MLCommons/results/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/multistream/accuracy/accuracy.txt +++ b/open/MLCommons/results/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/multistream/accuracy/accuracy.txt @@ -1,19 +1,19 @@ loading annotations into memory... -Done (t=0.44s) +Done (t=0.54s) creating index... index created! Loading and preparing results... -DONE (t=16.90s) +DONE (t=17.22s) creating index... index created! Running per image evaluation... Evaluate annotation type *bbox* -DONE (t=132.02s). +DONE (t=132.63s). Accumulating evaluation results... -DONE (t=31.61s). - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.374 +DONE (t=32.44s). + Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.373 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.522 - Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.404 + Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.403 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.022 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.125 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.413 @@ -21,11 +21,11 @@ DONE (t=31.61s). Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.599 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.628 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.082 - Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.345 - Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.678 -mAP=37.356% + Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.344 + Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.677 +mAP=37.327% found 24784 results found 24781 images found 0 images with no results ignored 3 dupes -hash=8a75a6624bd003e01ab7eb55147ba682b7272027a0a9b35fbfe3fbcca84ae6bc +hash=5933265f4faf3bb464a2081f2bd72b1278c2730725b66c041968f5b97ff7fb82 diff --git a/open/MLCommons/results/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/multistream/accuracy/mlperf_log_accuracy.json b/open/MLCommons/results/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/multistream/accuracy/mlperf_log_accuracy.json index 550e47f5..75f0985d 100644 --- a/open/MLCommons/results/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/multistream/accuracy/mlperf_log_accuracy.json +++ b/open/MLCommons/results/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/multistream/accuracy/mlperf_log_accuracy.json @@ -1,9 +1,9 @@ [ -{ "seq_id" : 0, "qsl_idx" : 13741, "data" : 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"value": 5619631, "time_ms": 602150.910132, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/94a57f78972843c6/repo/closed/NVIDIA/build/inference/loadgen/results.cc", "line_no": 691, "pid": 25471, "tid": 25471}} +:::MLLOG {"key": "result_99.90_percentile_per_query_latency_ns", "value": 5768951, "time_ms": 602150.910132, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/94a57f78972843c6/repo/closed/NVIDIA/build/inference/loadgen/results.cc", "line_no": 691, "pid": 25471, "tid": 25471}} +:::MLLOG {"key": "early_stopping_latency_ms", "value": 5623507, "time_ms": 602150.910132, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": 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"event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/94a57f78972843c6/repo/closed/NVIDIA/build/inference/loadgen/results.cc", "line_no": 743, "pid": 25471, "tid": 25471}} +:::MLLOG {"key": "result_50.00_percentile_latency_ns", "value": 5161747, "time_ms": 602150.910132, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/94a57f78972843c6/repo/closed/NVIDIA/build/inference/loadgen/results.cc", "line_no": 745, "pid": 25471, "tid": 25471}} +:::MLLOG {"key": "result_90.00_percentile_latency_ns", "value": 5357748, "time_ms": 602150.910132, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/94a57f78972843c6/repo/closed/NVIDIA/build/inference/loadgen/results.cc", "line_no": 745, "pid": 25471, "tid": 25471}} +:::MLLOG {"key": "result_95.00_percentile_latency_ns", "value": 5394887, "time_ms": 602150.910132, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/94a57f78972843c6/repo/closed/NVIDIA/build/inference/loadgen/results.cc", "line_no": 745, "pid": 25471, "tid": 25471}} +:::MLLOG {"key": "result_97.00_percentile_latency_ns", "value": 5422295, "time_ms": 602150.910132, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/94a57f78972843c6/repo/closed/NVIDIA/build/inference/loadgen/results.cc", "line_no": 745, "pid": 25471, "tid": 25471}} +:::MLLOG {"key": "result_99.00_percentile_latency_ns", "value": 5523765, "time_ms": 602150.910132, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/94a57f78972843c6/repo/closed/NVIDIA/build/inference/loadgen/results.cc", "line_no": 745, "pid": 25471, "tid": 25471}} +:::MLLOG {"key": "result_99.90_percentile_latency_ns", "value": 5673573, "time_ms": 602150.910132, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/94a57f78972843c6/repo/closed/NVIDIA/build/inference/loadgen/results.cc", "line_no": 745, "pid": 25471, "tid": 25471}} diff --git a/open/MLCommons/results/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/multistream/performance/run_1/mlperf_log_summary.txt b/open/MLCommons/results/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/multistream/performance/run_1/mlperf_log_summary.txt index d78db539..d1f796ba 100644 --- a/open/MLCommons/results/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/multistream/performance/run_1/mlperf_log_summary.txt +++ b/open/MLCommons/results/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/multistream/performance/run_1/mlperf_log_summary.txt @@ -4,29 +4,29 @@ MLPerf Results Summary SUT name : LWIS_Server Scenario : MultiStream Mode : PerformanceOnly -99th percentile latency (ns) : 5651849 +99th percentile latency (ns) : 5619631 Result is : VALID Min duration satisfied : Yes Min queries satisfied : Yes Early stopping satisfied: Yes Early Stopping Result: - * Processed at least 662 queries (111606). - * Would discard 1037 highest latency queries. - * Early stopping 99th percentile estimate: 5654438 + * Processed at least 662 queries (111862). + * Would discard 1040 highest latency queries. + * Early stopping 99th percentile estimate: 5623507 ================================================ Additional Stats ================================================ Per-query latency: -Min latency (ns) : 5214573 -Max latency (ns) : 8069045 -Mean latency (ns) : 5357942 -50.00 percentile latency (ns) : 5336429 -90.00 percentile latency (ns) : 5431391 -95.00 percentile latency (ns) : 5523050 -97.00 percentile latency (ns) : 5593377 -99.00 percentile latency (ns) : 5651849 -99.90 percentile latency (ns) : 5807528 +Min latency (ns) : 5202031 +Max latency (ns) : 8045809 +Mean latency (ns) : 5349062 +50.00 percentile latency (ns) : 5331934 +90.00 percentile latency (ns) : 5416248 +95.00 percentile latency (ns) : 5460941 +97.00 percentile latency (ns) : 5521612 +99.00 percentile latency (ns) : 5619631 +99.90 percentile latency (ns) : 5768951 ================================================ Test Parameters Used diff --git a/open/MLCommons/results/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/offline/accuracy/accuracy.txt b/open/MLCommons/results/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/offline/accuracy/accuracy.txt index 59650e68..1be6b340 100644 --- a/open/MLCommons/results/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/offline/accuracy/accuracy.txt +++ b/open/MLCommons/results/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/offline/accuracy/accuracy.txt @@ -1,31 +1,31 @@ loading annotations into memory... -Done (t=0.44s) +Done (t=0.45s) creating index... index created! Loading and preparing results... -DONE (t=17.15s) +DONE (t=17.03s) creating index... index created! Running per image evaluation... Evaluate annotation type *bbox* -DONE (t=133.60s). +DONE (t=132.32s). Accumulating evaluation results... -DONE (t=32.03s). +DONE (t=31.88s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.373 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.522 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.404 - Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.022 + Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.023 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.125 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.413 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.419 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.599 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.628 - Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.081 - Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.343 - Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.678 -mAP=37.332% + Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.083 + Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.344 + Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.677 +mAP=37.343% found 24781 results found 24781 images found 0 images with no results ignored 0 dupes -hash=bb5035db7b244a95d1d6806814b26154b6f51c69426ed1ed72fd1f307cb16ac9 +hash=ccf0017230212fe1fe726c4428d96604c85abb7926ce3b7999026a983050e0f5 diff --git a/open/MLCommons/results/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/offline/accuracy/mlperf_log_accuracy.json b/open/MLCommons/results/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/offline/accuracy/mlperf_log_accuracy.json index cf9750e1..f2d1749e 100644 --- a/open/MLCommons/results/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/offline/accuracy/mlperf_log_accuracy.json +++ b/open/MLCommons/results/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/offline/accuracy/mlperf_log_accuracy.json @@ -1,7 +1,7 @@ [ -{ "seq_id" : 0, "qsl_idx" : 4117, "data" : 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a/open/MLCommons/results/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/offline/performance/run_1/mlperf_log_detail.txt +++ b/open/MLCommons/results/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/offline/performance/run_1/mlperf_log_detail.txt @@ -1,85 +1,85 @@ -:::MLLOG {"key": "loadgen_version", "value": "4.0 @ 486a629ea4", "time_ms": 0.012389, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/94a57f78972843c6/repo/closed/NVIDIA/build/inference/loadgen/version.cc", "line_no": 53, "pid": 19677, "tid": 19677}} -:::MLLOG {"key": "loadgen_build_date_local", "value": "2024-12-23T01:12:58.514113", "time_ms": 0.012389, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": 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"file": "/home/cmuser/CM/repos/local/cache/94a57f78972843c6/repo/closed/NVIDIA/build/inference/loadgen/results.cc", "line_no": 745, "pid": 19680, "tid": 19680}} +:::MLLOG {"key": "result_99.00_percentile_latency_ns", "value": 647279408516, "time_ms": 653895.237784, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/94a57f78972843c6/repo/closed/NVIDIA/build/inference/loadgen/results.cc", "line_no": 745, "pid": 19680, "tid": 19680}} +:::MLLOG {"key": "result_99.90_percentile_latency_ns", "value": 653160102521, "time_ms": 653895.237784, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/94a57f78972843c6/repo/closed/NVIDIA/build/inference/loadgen/results.cc", "line_no": 745, "pid": 19680, "tid": 19680}} diff --git a/open/MLCommons/results/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/offline/performance/run_1/mlperf_log_summary.txt b/open/MLCommons/results/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/offline/performance/run_1/mlperf_log_summary.txt index 0604a466..47154720 100644 --- a/open/MLCommons/results/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/offline/performance/run_1/mlperf_log_summary.txt +++ b/open/MLCommons/results/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/offline/performance/run_1/mlperf_log_summary.txt @@ -4,7 +4,7 @@ MLPerf Results Summary SUT name : LWIS_Server Scenario : Offline Mode : PerformanceOnly -Samples per second: 1735.67 +Samples per second: 1733.25 Result is : VALID Min duration satisfied : Yes Min queries satisfied : Yes @@ -13,15 +13,15 @@ Result is : VALID ================================================ Additional Stats ================================================ -Min latency (ns) : 10103064 -Max latency (ns) : 652900040708 -Mean latency (ns) : 326059396190 -50.00 percentile latency (ns) : 326072726405 -90.00 percentile latency (ns) : 587467017824 -95.00 percentile latency (ns) : 620190413152 -97.00 percentile latency (ns) : 633278434850 -99.00 percentile latency (ns) : 646359997095 -99.90 percentile latency (ns) : 652246409070 +Min latency (ns) : 9596849 +Max latency (ns) : 653812127205 +Mean latency (ns) : 326581007159 +50.00 percentile latency (ns) : 326492917586 +90.00 percentile latency (ns) : 588415259666 +95.00 percentile latency (ns) : 621117225069 +97.00 percentile latency (ns) : 634197894873 +99.00 percentile latency (ns) : 647279408516 +99.90 percentile latency (ns) : 653160102521 ================================================ Test Parameters Used diff --git a/open/MLCommons/results/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/server/accuracy/accuracy.txt b/open/MLCommons/results/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/server/accuracy/accuracy.txt index 59b3f237..3019cf37 100644 --- a/open/MLCommons/results/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/server/accuracy/accuracy.txt +++ b/open/MLCommons/results/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/server/accuracy/accuracy.txt @@ -1,16 +1,16 @@ loading annotations into memory... -Done (t=0.47s) +Done (t=0.48s) creating index... index created! Loading and preparing results... -DONE (t=17.05s) +DONE (t=17.09s) creating index... index created! Running per image evaluation... Evaluate annotation type *bbox* -DONE (t=134.02s). +DONE (t=132.80s). Accumulating evaluation results... -DONE (t=32.36s). +DONE (t=31.81s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.373 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.522 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.404 @@ -20,12 +20,12 @@ DONE (t=32.36s). Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.419 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.599 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.628 - Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.081 + Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.082 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.344 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.678 -mAP=37.338% +mAP=37.345% found 24781 results found 24781 images found 0 images with no results ignored 0 dupes -hash=fc8e11f71f668bb3942038ad34e08be0f3ffa0a09935b3c4be2834fc01a6cd08 +hash=532c16c15fc18b1d51299b5043cb2faacbfc4be05e0544d33bcab2d0dfc84f4f diff --git a/open/MLCommons/results/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/server/accuracy/mlperf_log_accuracy.json b/open/MLCommons/results/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/server/accuracy/mlperf_log_accuracy.json index 8d98e8b2..de5a422f 100644 --- a/open/MLCommons/results/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/server/accuracy/mlperf_log_accuracy.json +++ b/open/MLCommons/results/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/server/accuracy/mlperf_log_accuracy.json @@ -1,8 +1,8 @@ [ -{ "seq_id" : 0, "qsl_idx" : 10615, "data" : 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a/open/MLCommons/results/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/server/performance/run_1/mlperf_log_detail.txt +++ b/open/MLCommons/results/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/server/performance/run_1/mlperf_log_detail.txt @@ -1,94 +1,94 @@ -:::MLLOG {"key": "loadgen_version", "value": "4.0 @ 486a629ea4", "time_ms": 0.008579, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/94a57f78972843c6/repo/closed/NVIDIA/build/inference/loadgen/version.cc", "line_no": 53, "pid": 32810, "tid": 32810}} -:::MLLOG {"key": "loadgen_build_date_local", "value": "2024-12-23T01:12:58.514113", "time_ms": 0.008579, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": 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600532.284071, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/94a57f78972843c6/repo/closed/NVIDIA/build/inference/loadgen/results.cc", "line_no": 745, "pid": 32815, "tid": 32815}} diff --git a/open/MLCommons/results/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/server/performance/run_1/mlperf_log_summary.txt b/open/MLCommons/results/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/server/performance/run_1/mlperf_log_summary.txt index c68a6037..7c2027e6 100644 --- a/open/MLCommons/results/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/server/performance/run_1/mlperf_log_summary.txt +++ b/open/MLCommons/results/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/server/performance/run_1/mlperf_log_summary.txt @@ -16,17 +16,17 @@ Early Stopping Result: ================================================ Additional Stats ================================================ -Completed samples per second : 1415.00 +Completed samples per second : 1414.99 -Min latency (ns) : 2791060 -Max latency (ns) : 31466339 -Mean latency (ns) : 13782929 -50.00 percentile latency (ns) : 13537376 -90.00 percentile latency (ns) : 17064287 -95.00 percentile latency (ns) : 18129749 -97.00 percentile latency (ns) : 18822106 -99.00 percentile latency (ns) : 20235023 -99.90 percentile latency (ns) : 23653280 +Min latency (ns) : 2742550 +Max latency (ns) : 31247479 +Mean latency (ns) : 13785689 +50.00 percentile latency (ns) : 13540363 +90.00 percentile latency (ns) : 17065882 +95.00 percentile latency (ns) : 18127387 +97.00 percentile latency (ns) : 18824906 +99.00 percentile latency (ns) : 20222769 +99.90 percentile latency (ns) : 23596887 ================================================ Test Parameters Used diff --git a/open/MLCommons/results/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/singlestream/accuracy/accuracy.txt b/open/MLCommons/results/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/singlestream/accuracy/accuracy.txt index 64ceeded..4180aea3 100644 --- a/open/MLCommons/results/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/singlestream/accuracy/accuracy.txt +++ b/open/MLCommons/results/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/singlestream/accuracy/accuracy.txt @@ -3,29 +3,29 @@ Done (t=0.52s) creating index... index created! Loading and preparing results... -DONE (t=17.08s) +DONE (t=17.29s) creating index... index created! Running per image evaluation... Evaluate annotation type *bbox* -DONE (t=132.30s). +DONE (t=132.94s). Accumulating evaluation results... -DONE (t=32.33s). - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.374 - Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.523 - Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.404 +DONE (t=31.82s). + Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.373 + Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.522 + Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.403 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.023 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.125 - Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.413 - Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.420 - Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.599 - Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.628 - Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.082 - Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.343 - Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.678 -mAP=37.366% + Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.412 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.419 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.598 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.627 + Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.083 + Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.344 + Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.677 +mAP=37.297% found 24781 results found 24781 images found 0 images with no results ignored 0 dupes -hash=846221cbc391636b2826a60955cbb86be7fe76321f5e3d90b2bed67d3ab5ba9d +hash=b2a56b0637ebfa74655b586d3692a747bd0df88e92adf902137ee220ad81849a diff --git a/open/MLCommons/results/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/singlestream/accuracy/mlperf_log_accuracy.json b/open/MLCommons/results/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/singlestream/accuracy/mlperf_log_accuracy.json index 36f531bb..b2744982 100644 --- a/open/MLCommons/results/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/singlestream/accuracy/mlperf_log_accuracy.json +++ b/open/MLCommons/results/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/singlestream/accuracy/mlperf_log_accuracy.json @@ -1,8 +1,8 @@ [ -{ "seq_id" : 0, "qsl_idx" : 10615, "data" : 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"tid": 12084}} +:::MLLOG {"key": "generated_samples_per_query", "value": 1, "time_ms": 1355.727243, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/94a57f78972843c6/repo/closed/NVIDIA/build/inference/loadgen/loadgen.cc", "line_no": 429, "pid": 12084, "tid": 12084}} +:::MLLOG {"key": "generated_query_duration", "value": 1200000500000, "time_ms": 1355.727243, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/94a57f78972843c6/repo/closed/NVIDIA/build/inference/loadgen/loadgen.cc", "line_no": 430, "pid": 12084, "tid": 12084}} +:::MLLOG {"key": "generic_message", "value": "Ending naturally: Minimum query count and test duration met.", "time_ms": 601356.029321, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/94a57f78972843c6/repo/closed/NVIDIA/build/inference/loadgen/issue_query_controller.cc", "line_no": 482, "pid": 12084, "tid": 12084}} +:::MLLOG {"key": "logger_swap_request_slots_retry_count", "value": 0, "time_ms": 601360.023429, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/94a57f78972843c6/repo/closed/NVIDIA/build/inference/loadgen/logging.cc", "line_no": 898, "pid": 12084, "tid": 12084}} +:::MLLOG {"key": "logger_swap_request_slots_retry_retry_count", "value": 0, "time_ms": 601360.023429, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/94a57f78972843c6/repo/closed/NVIDIA/build/inference/loadgen/logging.cc", "line_no": 900, "pid": 12084, "tid": 12084}} +:::MLLOG {"key": "logger_swap_request_slots_retry_reencounter_count", "value": 0, "time_ms": 601360.023429, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/94a57f78972843c6/repo/closed/NVIDIA/build/inference/loadgen/logging.cc", "line_no": 902, "pid": 12084, "tid": 12084}} +:::MLLOG {"key": "logger_start_reading_entries_retry_count", "value": 0, "time_ms": 601360.023429, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/94a57f78972843c6/repo/closed/NVIDIA/build/inference/loadgen/logging.cc", "line_no": 904, "pid": 12084, "tid": 12084}} +:::MLLOG {"key": "logger_tls_total_log_cas_fail_count", "value": 0, "time_ms": 601360.023429, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/94a57f78972843c6/repo/closed/NVIDIA/build/inference/loadgen/logging.cc", "line_no": 906, "pid": 12084, "tid": 12084}} +:::MLLOG {"key": "logger_tls_total_swap_buffers_slot_retry_count", "value": 0, "time_ms": 601360.023429, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/94a57f78972843c6/repo/closed/NVIDIA/build/inference/loadgen/logging.cc", "line_no": 908, "pid": 12084, "tid": 12084}} +:::MLLOG {"key": "power_begin", "value": "12-25-2024 08:23:57.212", "time_ms": 601360.024435, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/94a57f78972843c6/repo/closed/NVIDIA/build/inference/loadgen/loadgen.cc", "line_no": 564, "pid": 12084, "tid": 12084}} +:::MLLOG {"key": "power_end", "value": "12-25-2024 08:33:57.214", "time_ms": 601360.024435, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/94a57f78972843c6/repo/closed/NVIDIA/build/inference/loadgen/loadgen.cc", "line_no": 566, "pid": 12084, "tid": 12084}} +:::MLLOG {"key": "result_validity", "value": "VALID", "time_ms": 601735.287979, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/94a57f78972843c6/repo/closed/NVIDIA/build/inference/loadgen/results.cc", "line_no": 644, "pid": 12084, "tid": 12084}} +:::MLLOG {"key": "result_min_duration_met", "value": true, "time_ms": 601735.287979, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/94a57f78972843c6/repo/closed/NVIDIA/build/inference/loadgen/results.cc", "line_no": 649, "pid": 12084, "tid": 12084}} +:::MLLOG {"key": "result_min_queries_met", "value": true, "time_ms": 601735.287979, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/94a57f78972843c6/repo/closed/NVIDIA/build/inference/loadgen/results.cc", "line_no": 650, "pid": 12084, "tid": 12084}} +:::MLLOG {"key": "early_stopping_met", "value": true, "time_ms": 601735.287979, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/94a57f78972843c6/repo/closed/NVIDIA/build/inference/loadgen/results.cc", "line_no": 651, "pid": 12084, "tid": 12084}} +:::MLLOG {"key": "early_stopping_result", "value": " * Processed at least 64 queries (351200). * Would discard 34705 highest latency queries. * Early stopping 90th percentile estimate: 1735586 * Early stopping 99th percentile estimate: 1807521", "time_ms": 601735.287979, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/94a57f78972843c6/repo/closed/NVIDIA/build/inference/loadgen/results.cc", "line_no": 669, "pid": 12084, "tid": 12084}} +:::MLLOG {"key": "result_query_count", "value": 351200, "time_ms": 601735.287979, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/94a57f78972843c6/repo/closed/NVIDIA/build/inference/loadgen/results.cc", "line_no": 679, "pid": 12084, "tid": 12084}} +:::MLLOG {"key": "result_qps_with_loadgen_overhead", "value": 585.331, "time_ms": 601735.287979, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/94a57f78972843c6/repo/closed/NVIDIA/build/inference/loadgen/results.cc", "line_no": 702, "pid": 12084, "tid": 12084}} +:::MLLOG {"key": "result_qps_without_loadgen_overhead", "value": 589.083, "time_ms": 601735.287979, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/94a57f78972843c6/repo/closed/NVIDIA/build/inference/loadgen/results.cc", "line_no": 703, "pid": 12084, "tid": 12084}} +:::MLLOG {"key": "early_stopping_latency_ss", "value": 1735586, "time_ms": 601735.287979, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/94a57f78972843c6/repo/closed/NVIDIA/build/inference/loadgen/results.cc", "line_no": 704, "pid": 12084, "tid": 12084}} +:::MLLOG {"key": "early_stopping_latency_ms", "value": 1807521, "time_ms": 601735.287979, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/94a57f78972843c6/repo/closed/NVIDIA/build/inference/loadgen/results.cc", "line_no": 706, "pid": 12084, "tid": 12084}} +:::MLLOG {"key": "result_min_latency_ns", "value": 1631869, "time_ms": 601735.287979, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/94a57f78972843c6/repo/closed/NVIDIA/build/inference/loadgen/results.cc", "line_no": 741, "pid": 12084, "tid": 12084}} +:::MLLOG {"key": "result_max_latency_ns", "value": 2071005, "time_ms": 601735.287979, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/94a57f78972843c6/repo/closed/NVIDIA/build/inference/loadgen/results.cc", "line_no": 742, "pid": 12084, "tid": 12084}} +:::MLLOG {"key": "result_mean_latency_ns", "value": 1697554, "time_ms": 601735.287979, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/94a57f78972843c6/repo/closed/NVIDIA/build/inference/loadgen/results.cc", "line_no": 743, "pid": 12084, "tid": 12084}} +:::MLLOG {"key": "result_50.00_percentile_latency_ns", "value": 1691179, "time_ms": 601735.287979, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/94a57f78972843c6/repo/closed/NVIDIA/build/inference/loadgen/results.cc", "line_no": 745, "pid": 12084, "tid": 12084}} +:::MLLOG {"key": "result_90.00_percentile_latency_ns", "value": 1735339, "time_ms": 601735.287979, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/94a57f78972843c6/repo/closed/NVIDIA/build/inference/loadgen/results.cc", "line_no": 745, "pid": 12084, "tid": 12084}} +:::MLLOG {"key": "result_95.00_percentile_latency_ns", "value": 1753792, "time_ms": 601735.287979, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/94a57f78972843c6/repo/closed/NVIDIA/build/inference/loadgen/results.cc", "line_no": 745, "pid": 12084, "tid": 12084}} +:::MLLOG {"key": "result_97.00_percentile_latency_ns", "value": 1772192, "time_ms": 601735.287979, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/94a57f78972843c6/repo/closed/NVIDIA/build/inference/loadgen/results.cc", "line_no": 745, "pid": 12084, "tid": 12084}} +:::MLLOG {"key": "result_99.00_percentile_latency_ns", "value": 1806957, "time_ms": 601735.287979, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/94a57f78972843c6/repo/closed/NVIDIA/build/inference/loadgen/results.cc", "line_no": 745, "pid": 12084, "tid": 12084}} +:::MLLOG {"key": "result_99.90_percentile_latency_ns", "value": 1841780, "time_ms": 601735.287979, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/94a57f78972843c6/repo/closed/NVIDIA/build/inference/loadgen/results.cc", "line_no": 745, "pid": 12084, "tid": 12084}} diff --git a/open/MLCommons/results/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/singlestream/performance/run_1/mlperf_log_summary.txt b/open/MLCommons/results/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/singlestream/performance/run_1/mlperf_log_summary.txt index 80b21df0..c935115a 100644 --- a/open/MLCommons/results/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/singlestream/performance/run_1/mlperf_log_summary.txt +++ b/open/MLCommons/results/RTX4090x2-nvidia_original-gpu-tensorrt-vdefault-default_config/retinanet/singlestream/performance/run_1/mlperf_log_summary.txt @@ -4,32 +4,32 @@ MLPerf Results Summary SUT name : LWIS_Server Scenario : SingleStream Mode : PerformanceOnly -90th percentile latency (ns) : 1735993 +90th percentile latency (ns) : 1735339 Result is : VALID Min duration satisfied : Yes Min queries satisfied : Yes Early stopping satisfied: Yes Early Stopping Result: - * Processed at least 64 queries (350949). - * Would discard 34680 highest latency queries. - * Early stopping 90th percentile estimate: 1736348 - * Early stopping 99th percentile estimate: 1809454 + * Processed at least 64 queries (351200). + * Would discard 34705 highest latency queries. + * Early stopping 90th percentile estimate: 1735586 + * Early stopping 99th percentile estimate: 1807521 ================================================ Additional Stats ================================================ -QPS w/ loadgen overhead : 584.91 -QPS w/o loadgen overhead : 588.72 +QPS w/ loadgen overhead : 585.33 +QPS w/o loadgen overhead : 589.08 -Min latency (ns) : 1629520 -Max latency (ns) : 2213670 -Mean latency (ns) : 1698601 -50.00 percentile latency (ns) : 1691995 -90.00 percentile latency (ns) : 1735993 -95.00 percentile latency (ns) : 1755102 -97.00 percentile latency (ns) : 1775037 -99.00 percentile latency (ns) : 1808927 -99.90 percentile latency (ns) : 1869184 +Min latency (ns) : 1631869 +Max latency (ns) : 2071005 +Mean latency (ns) : 1697554 +50.00 percentile latency (ns) : 1691179 +90.00 percentile latency (ns) : 1735339 +95.00 percentile latency (ns) : 1753792 +97.00 percentile latency (ns) : 1772192 +99.00 percentile latency (ns) : 1806957 +99.90 percentile latency (ns) : 1841780 ================================================ Test Parameters Used