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Results in a very long Blush runs (from 1.5 to 8h) as shown here:
2024-12-20 15:53:27.907 | INFO | relion_blush.command_line:main:271 - ARGUMENTS: Namespace(star_file='Refine3D/job006/run_it008_half1_class001_external_reconstruct.star', model_name='v1.0', strides=20, batch_size=1, gpu=',', device_timeout=1200, debug=False, skip_spectral_trailing=False)
2024-12-20 15:53:28.100 | INFO | relion_blush.command_line:main:283 - Loading model time 0.19 s
2024-12-20 17:26:10.000 | INFO | relion_blush.command_line:main:315 - Selected device: cpu
2024-12-20 17:26:10.887 | INFO | relion_blush.command_line:refine3d:44 - Resample time 0.89 s
2024-12-20 17:26:11.257 | INFO | relion_blush.command_line:refine3d:57 - Volume preprocess rescale time 0.37 s
2024-12-20 17:26:11.369 | INFO | relion_blush.command_line:refine3d:74 - Radial masks time 0.11 s
2024-12-20 17:28:14.290 | INFO | relion_blush.command_line:refine3d:87 - Running model time 122.92 s
2024-12-20 17:28:14.611 | INFO | relion_blush.command_line:refine3d:97 - Post-processing rescale time 0.32 s
2024-12-20 17:28:14.611 | INFO | relion_blush.command_line:refine3d:131 - Applying spectral trailing
2024-12-20 17:28:14.622 | INFO | relion_blush.command_line:refine3d:135 - Max denoised spectral index: 39
2024-12-20 17:28:14.622 | INFO | relion_blush.command_line:refine3d:138 - Max denoised resolution: 9.85
2024-12-20 17:28:14.686 | INFO | relion_blush.command_line:refine3d:155 - Ouput to file Refine3D/job006/run_it008_half1_class001_external_reconstruct.mrc
The identified issue might be the 2024-12-20 17:26:10.000 | INFO | relion_blush.command_line:main:315 - Selected device: cpu. However, when the Python environement is loaded, and this is executed:
import torch
# Check if GPU is available
if torch.cuda.is_available():
print("GPU is available!")
device = torch.device("cuda")
else:
print("GPU is not available, using CPU")
device = torch.device("cpu")
# Print the current device
print(f"Using device: {device}")
# Get information about the GPU (if available)
if torch.cuda.is_available():
print(f"GPU name: {torch.cuda.get_device_name(0)}")
print(f"Number of GPUs: {torch.cuda.device_count()}")
It correctly shows the number of GPUs detected, and Torch supports CUDA. Is there any easy solution to make Blush run faster?
Environment:
OS: Rocky Linux release 8.6 (Green Obsidian)
MPI runtime: mpirun (Open MPI) 4.1.1
RELION version 5.0.0
Memory: Cluster / 128/256
GPU: 2080ti/A40
The text was updated successfully, but these errors were encountered:
@dzyla Meanwhile, probably you can workaround this issue by explicitly specifying GPU IDs in the RELION GUI. For example, if you have 2 GPUs and 5 MPI processes, specify "0:1:0:1".
@biochem-fan,
Thank you very much for getting back to us so quickly. Specifying 0:1:2:3 (4 GPU), now maximization steps are done in 18 sec! Thank you very much for getting back to me so quickly. It was a great suggestion.
Describe your problem
Please write a clear description of what the problem is.
Running 3D refinement in
relion --tomo
using this command:which relion_refine_mpi` --continue Refine3D/job006/run_it007_optimiser.star --o Refine3D/job006/run --blush --dont_combine_weights_via_disc --pool 3 --pad 2 --particle_diameter 240 --solvent_mask MaskCreate/job004/mask.mrc --solvent_correct_fsc --j 6 --gpu "" --pipeline_control Refine3D/job006/
Results in a very long Blush runs (from 1.5 to 8h) as shown here:
The identified issue might be the
2024-12-20 17:26:10.000 | INFO | relion_blush.command_line:main:315 - Selected device: cpu
. However, when the Python environement is loaded, and this is executed:It correctly shows the number of GPUs detected, and Torch supports CUDA. Is there any easy solution to make Blush run faster?
Environment:
The text was updated successfully, but these errors were encountered: