From a1d97523db960cc962a33e462498e249665fa890 Mon Sep 17 00:00:00 2001
From: "atharva.dubey" <atharva.dubey@codeplay.com>
Date: Tue, 22 Oct 2024 16:53:41 +0100
Subject: [PATCH] restore quickstart.md

---
 media/docs/quickstart.md | 46 +---------------------------------------
 1 file changed, 1 insertion(+), 45 deletions(-)

diff --git a/media/docs/quickstart.md b/media/docs/quickstart.md
index 923cae4b6b..7faad445d9 100644
--- a/media/docs/quickstart.md
+++ b/media/docs/quickstart.md
@@ -11,8 +11,6 @@ CUTLASS requires:
 - CMake 3.18+
 - host compiler supporting C++17 or greater (minimum g++ 7.5.0)
 - Python 3.6+
-- For the SYCL backend, an installation of the open source `DPC++` compiler, which 
-  can be found [here](https://github.com/intel/llvm)
 
 CUTLASS may be optionally compiled and linked with
 - cuBLAS
@@ -20,7 +18,7 @@ CUTLASS may be optionally compiled and linked with
 
 ## Initial build steps
 
-Construct a build directory and run CMake if using the CUDA toolchain.
+Construct a build directory and run CMake.
 ```bash
 $ export CUDACXX=${CUDA_INSTALL_PATH}/bin/nvcc
 
@@ -29,48 +27,6 @@ $ mkdir build && cd build
 $ cmake .. -DCUTLASS_NVCC_ARCHS=90a             # compiles for NVIDIA Hopper GPU architecture
 ```
 
-## Building and Running on the SYCL backend
-To build with the Intel open source `DPC++` compiler when using the SYCL backend
-```bash
-$ mkdir build && cd build
-
-$ cmake -DCMAKE_CXX_COMPILER=clang++ -DCMAKE_C_COMPILER=clang -DCUTLASS_ENABLE_SYCL=ON -DDPCPP_SYCL_TARGET=nvptx64-nvidia-cuda -DDPCPP_SYCL_ARCH=sm_80 .. # compiles for the NVIDIA Ampere GPU architecture
-
-# compiles for the Intel PVC Architecture
-cmake -DCUTLASS_ENABLE_SYCL=ON -DDPCPP_SYCL_TARGET=intel_gpu_pvc ..
-```
-A complete example can be as follows (running on the Intel Data Center Max 1100) - 
-
-```bash
-$ cmake -DCMAKE_CXX_COMPILER=clang++ -DCMAKE_C_COMPILER=clang -DCUTLASS_ENABLE_SYCL=ON -DDPCPP_SYCL_TARGET=intel_gpu_pvc ..
-
-$ make pvc_gemm
-
-$ ./examples/sycl/pvc/pvc_gemm
-
-Disposition: Passed
-Problem Size: 5120x4096x4096x1
-Cutlass GEMM Performance:     [225.773]TFlop/s  (0.7609)ms
-```
-More examples on the Intel GPU can be found in the [sycl example folder](../../examples/sycl/pvc/)
-
-A complete example when running on a A100, using the SYCL backend
-
-```bash
-$ cmake -DCMAKE_CXX_COMPILER=clang++ -DCMAKE_C_COMPILER=clang -DCUTLASS_ENABLE_SYCL=ON -DDPCPP_SYCL_TARGET=nvptx64-nvidia-cuda -DDPCPP_SYCL_ARCH=sm_80
-
-$ make 14_ampere_tf32_tensorop_gemm_cute
-
-$ ./examples/14_ampere_tf32_tensorop_gemm/14_ampere_tf32_tensorop_gemm_cute 
-
-  Disposition: Passed
-  Problem Size: 5120x4096x4096x1
-  Avg runtime: 1.5232 ms
-  GFLOPS: 112788
-```
-
-### CUTLASS quick building  tips
-
 If your goal is strictly to build only the CUTLASS Profiler and to minimize compilation time, we suggest
 executing the following CMake command in an empty `build/` directory.
 ```bash