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* New version of the GPU programming section. * Added abstractions. * Added OneProf * Added GPU programming wiht Julia.
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| # OpenCL & CUDA | ||
| # GPU Programming Languages | ||
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| *Page maintainer: Alessio Sclocco* [@isazi](https://github.com/isazi) | ||
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| ## Sources for learning | ||
| *please add university courses and informative videos* | ||
| * Parallel Reduction [[Slides](http://developer.download.nvidia.com/compute/cuda/1.1-Beta/x86_website/projects/reduction/doc/reduction.pdf)] | ||
| * GPU Memory bootcamp - Tony Scudiero [[git repo](https://github.com/tscudiero/MemBootcamp)] | ||
| * Best Practices [[Slides](https://github.com/tscudiero/MemBootcamp/blob/master/Slides/S5353_Scudiero_Bootcamp1.pdf)] [[Video](http://on-demand.gputechconf.com/gtc/2015/video/S5353.html)] | ||
| * Beyond the Best Practices [[Slides](https://github.com/tscudiero/MemBootcamp/blob/master/Slides/S5376-Scudiero_Bootcamp2.pdf)] [[Video](http://on-demand.gputechconf.com/gtc/2015/video/S5376.html)] | ||
| * Collaborative Access Patterns [[Slides](https://github.com/tscudiero/MemBootcamp/blob/master/Slides/S6181-Scudiero_Bootcamp3.pdf)] [[Video](http://on-demand.gputechconf.com/gtc/2016/video/s6181-tony-scudiero-bootcamp-3.mp4)] | ||
| * CUB: CUDA Collective primitives library [[Git](https://github.com/NVlabs/cub)] [[Slides](http://on-demand.gputechconf.com/gtc/2015/presentation/S5617-Duane-Merrill.pdf)] [[Video](http://on-demand.gputechconf.com/gtc/2015/video/S5617.html)] | ||
| * Best Practices Guide by PRACE [[HTML](https://prace-ri.eu/training-support/best-practice-guides/best-practice-guide-gpgpu/)] [[PDF](https://prace-ri.eu/wp-content/uploads/Best-Practice-Guide_GPGPU.pdf)] | ||
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| ## Learning Resources | ||
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| * Carpentries GPU Programming course | ||
| * [Lesson material](https://carpentries-incubator.github.io/lesson-gpu-programming/) | ||
| * Introduction to CUDA C | ||
| * [Slides](http://developer.download.nvidia.com/compute/developertrainingmaterials/presentations/cuda_language/Introduction_to_CUDA_C.pptx) | ||
| * [Video](http://on-demand.gputechconf.com/gtc/2012/video/S0624-Monday-Introduction-to-CUDA-C.mp4) | ||
| * Introduction to OpenACC | ||
| * [Slides](http://developer.download.nvidia.com/compute/developertrainingmaterials/presentations/openacc/Introduction_To_OpenACC.pptx) | ||
| * Introduction to HIP Programming | ||
| * [Video](https://www.youtube.com/watch?v=3ejUwypP0bI) | ||
| * SYCL Introduction and Best Practices | ||
| * [Video](https://www.youtube.com/watch?v=TbkrODiVDQY) | ||
| * CSCS GPU Programming with Julia | ||
| * [Course recordings](https://github.com/omlins/julia-gpu-course) | ||
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| ## Documentation | ||
| * OpenCL specification [[1.2](https://www.khronos.org/registry/cl/sdk/1.2/docs/man/xhtml/)] [[2.0](https://www.khronos.org/registry/cl/sdk/2.0/docs/man/xhtml/)] | ||
| * CUDA Toolkit [[latest](http://docs.nvidia.com/cuda/index.html)] | ||
| * [CUDA Programming Guide](http://docs.nvidia.com/cuda/cuda-c-programming-guide/index.html) | ||
| * [CUDA Runtime API](http://docs.nvidia.com/cuda/cuda-runtime-api/index.html) | ||
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| ## Source-to-source translation between CUDA and OpenCL | ||
| * vtsynergy (https://github.com/vtsynergy) | ||
| * This was shown to work on DAS5 after copying /usr/include/limits.h to $PWD and commenting out the lines around # include_next (122-125) : | ||
| "cu2cl-tool host_code.cc device_code.cu -- -DGPU_ON -I$PWD:/usr/include -I/usr/lib/gcc/x86_64-redhat-linux/4.8.2/include". | ||
| * cutocl (https://github.com/benvanwerkhoven/cutocl) | ||
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| ## Overview of libraries | ||
| * OpenCL-based libraries | ||
| * [CLBlast](https://github.com/CNugteren/CLBlast) | ||
| * [clFFT](https://github.com/clMathLibraries/clFFT) | ||
| * CUDA-based libraries | ||
| * CUDA | ||
| * [C programming guide](https://docs.nvidia.com/cuda/cuda-c-programming-guide/index.html) | ||
| * [Runtime API](https://docs.nvidia.com/cuda/cuda-runtime-api/) | ||
| * [Driver API](https://docs.nvidia.com/cuda/cuda-driver-api/index.html) | ||
| * [Fortran programming guide](https://docs.nvidia.com/hpc-sdk/compilers/cuda-fortran-prog-guide/index.html) | ||
| * HIP | ||
| * [Kernel language syntax](https://rocm.docs.amd.com/projects/HIP/en/latest/reference/kernel_language.html) | ||
| * [Runtime API](https://rocm.docs.amd.com/projects/HIP/en/latest/.doxygen/docBin/html/modules.html) | ||
| * SYCL | ||
| * [Specification](https://registry.khronos.org/SYCL/specs/sycl-2020/html/sycl-2020.html) | ||
| * [Reference guide](https://www.khronos.org/files/sycl/sycl-2020-reference-guide.pdf) | ||
| * OpenCL | ||
| * [Guide](https://github.com/KhronosGroup/OpenCL-Guide) | ||
| * [API](https://registry.khronos.org/OpenCL/specs/3.0-unified/html/OpenCL_API.html) | ||
| * [OpenCL C specification](https://registry.khronos.org/OpenCL/specs/3.0-unified/html/OpenCL_C.html) | ||
| * [Reference guide](https://www.khronos.org/files/opencl30-reference-guide.pdf) | ||
| * OpenACC | ||
| * [Programming guide](https://www.openacc.org/sites/default/files/inline-files/OpenACC_Programming_Guide_0_0.pdf) | ||
| * [Reference guide](https://www.openacc.org/sites/default/files/inline-files/API%20Guide%202.7.pdf) | ||
| * OpenMP | ||
| * [Reference guide](https://www.openmp.org/wp-content/uploads/OpenMPRef-5.0-111802-web.pdf) | ||
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| ## Overview of Libraries | ||
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| * CUDA | ||
| * [cuBLAS](http://docs.nvidia.com/cuda/cublas/index.html) | ||
| * [NVBLAS](http://docs.nvidia.com/cuda/nvblas/index.html) | ||
| * [cuFFT](http://docs.nvidia.com/cuda/cufft/index.html) | ||
| * [cuGRAPH](https://docs.rapids.ai/api/cugraph/stable/) | ||
| * [cuRAND](http://docs.nvidia.com/cuda/curand/index.html) | ||
| * [cuSPARSE](http://docs.nvidia.com/cuda/cusparse/index.html) | ||
| * HIP | ||
| * [hipBLAS](https://rocm.docs.amd.com/projects/hipBLAS/en/latest/index.html) | ||
| * [hipFFT](https://rocm.docs.amd.com/projects/hipFFT/en/latest/index.html) | ||
| * [hipRAND](https://rocm.docs.amd.com/projects/hipRAND/en/latest/index.html) | ||
| * [hipSPARSE](https://rocm.docs.amd.com/projects/hipSPARSE/en/latest/index.html) | ||
| * SYCL | ||
| * [OneAPI BLAS](https://www.intel.com/content/www/us/en/docs/onemkl/developer-reference-dpcpp/2024-0/blas-routines.html#GUID-F277361F-49BA-437B-8100-3D2B6BBC3CC1) | ||
| * [OneAPI FFT](https://www.intel.com/content/www/us/en/docs/onemkl/developer-reference-dpcpp/2024-0/fourier-transform-functions.html#GUID-BB8891E9-D3D3-40B9-BBB1-2390C4340CDA) | ||
| * [OneAPI sparse](https://www.intel.com/content/www/us/en/docs/onemkl/developer-reference-dpcpp/2024-0/sparse-blas-routines.html#GUID-7123D31B-9C7F-4BA7-9792-02A417293E60) | ||
| * [OneAPI random number generators](https://www.intel.com/content/www/us/en/docs/onemkl/developer-reference-dpcpp/2024-0/random-number-generators.html#GUID-FFC80D12-C323-4A9F-83E3-D0ACDB686876) | ||
| * OpenCL | ||
| * [CLBlast](https://github.com/CNugteren/CLBlast) | ||
| * [clFFT](https://github.com/clMathLibraries/clFFT) | ||
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| ## Source-to-source Translation | ||
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| * CUDA to HIP | ||
| * [hipify](https://github.com/ROCm/HIPIFY) | ||
| * CUDA to SYCL | ||
| * [SYCLomatic](https://github.com/oneapi-src/SYCLomatic) | ||
| * CUDA to OpenCL | ||
| * [cutocl](https://github.com/benvanwerkhoven/cutocl) | ||
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| ## Foreign Function Interfaces | ||
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| * C++ | ||
| * CUDA | ||
| * [cudawrappers](https://github.com/nlesc-recruit/cudawrappers) | ||
| * OpenCL | ||
| * [CLHPP](https://github.com/KhronosGroup/OpenCL-CLHPP) | ||
| * Python | ||
| * CUDA | ||
| * [PyCuda](https://mathema.tician.de/software/pycuda/) | ||
| * [CuPy](https://cupy.dev/) | ||
| * [cuda-python](https://nvidia.github.io/cuda-python/) | ||
| * HIP | ||
| * [PyHIP](https://github.com/jatinx/PyHIP) | ||
| * SYCL | ||
| * [dpctl](https://github.com/IntelPython/dpctl) | ||
| * OpenCL | ||
| * [PyOpenCL](https://mathema.tician.de/software/pycuda/) | ||
| * Julia | ||
| * CUDA | ||
| * [CUDA.jl](https://github.com/JuliaGPU/CUDA.jl) | ||
| * HIP | ||
| * [AMDGPU.jl](https://github.com/JuliaGPU/AMDGPU.jl) | ||
| * SYCL | ||
| * [oneAPI.jl](https://github.com/JuliaGPU/oneAPI.jl) | ||
| * Java | ||
| * CUDA | ||
| * [JCuda](http://www.jcuda.org/) | ||
| * OpenCL | ||
| * [JOCL](http://www.jocl.org/) | ||
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| ## High-Level Abstractions | ||
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| * C++ | ||
| * [Kokkos](https://github.com/kokkos/kokkos) | ||
| * [Raja](https://github.com/LLNL/RAJA) | ||
| * Python | ||
| * [Numba](https://numba.pydata.org/) | ||
| * [pykokkos](https://github.com/kokkos/pykokkos) | ||
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| ## Foreign Function Interfaces for CUDA and OpenCL | ||
| * C++: [[Cuda](https://github.com/eyalroz/cuda-api-wrappers/)], [[OpenCL](https://github.com/KhronosGroup/OpenCL-CLHPP)] | ||
| * Python: [[PyCuda](https://mathema.tician.de/software/pycuda/)], [[PyOpenCL](https://mathema.tician.de/software/pycuda/)] | ||
| * Java: [[JCuda](http://www.jcuda.org/)], [[JOCL](http://www.jocl.org/)] | ||
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| ## Debugging and Profiling Tools | ||
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| ## Testing | ||
| * Unit Testing | ||
| * Example of a unit test for CUDA kernel using the [Kernel Tuner](https://github.com/benvanwerkhoven/kernel_tuner/blob/master/examples/cuda/test_vector_add.py) | ||
| * [comparing floating-point results](http://docs.nvidia.com/cuda/floating-point/index.html) | ||
| * CUDA | ||
| * [Nsight Systems](https://developer.nvidia.com/nsight-systems) | ||
| * [Nsight Compute](https://developer.nvidia.com/nsight-compute) | ||
| * [CUDA-GDB](http://docs.nvidia.com/cuda/cuda-gdb/index.html) | ||
| * [compute-sanitizer](https://docs.nvidia.com/compute-sanitizer/index.html) | ||
| * HIP | ||
| * [omniperf](https://github.com/AMDResearch/omniperf) | ||
| * [rocprof](https://github.com/ROCm/rocprofiler) | ||
| * SYCL | ||
| * [oneprof](https://github.com/intel/pti-gpu/tree/master/tools/oneprof) | ||
| * [onetrace](https://github.com/intel/pti-gpu/tree/master/tools/onetrace) | ||
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| ## Performance Optimization | ||
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| ## Debugging and Profiling Tools | ||
| * [Nvidia Visual Profiler](https://developer.nvidia.com/nvidia-visual-profiler) [[User Guide](http://docs.nvidia.com/cuda/profiler-users-guide)] | ||
| * [CUDA-GDB](http://docs.nvidia.com/cuda/cuda-gdb/index.html) | ||
| * [compute-sanitizer](https://docs.nvidia.com/cuda/compute-sanitizer/index.html) | ||
| * [PRACE best practice guide on modern accelerators](https://zenodo.org/records/5839488) | ||
| * [CUDA best practices](https://docs.nvidia.com/cuda/cuda-c-best-practices-guide/index.html) | ||
| * [OneAPI SYCL best practices](https://www.intel.com/content/www/us/en/docs/oneapi/programming-guide/2023-2/optimize-your-sycl-applications.html) | ||
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| ## Auto-tuning | ||
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| ## Performance Optimization | ||
| * Resources: | ||
| * Better Performance at Lower Occupancy [[Slides](http://www.nvidia.com/content/gtc-2010/pdfs/2238_gtc2010.pdf)] [[Video](http://on-demand.gputechconf.com/gtc/2010/video/S12238-Better-Performance-at-Lower-Occupancy.mp4)] | ||
| * [Maxwell Tuning Guide](http://docs.nvidia.com/cuda/maxwell-tuning-guide) | ||
| * [Pascal Tuning Guide](http://docs.nvidia.com/cuda/pascal-tuning-guide) | ||
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| * Generic Auto Tuners: | ||
| * [Kernel Tuner](https://github.com/benvanwerkhoven/kernel_tuner) (Python) | ||
| * [CLTune](https://github.com/CNugteren/CLTune) (C++) | ||
| * Kernel Tuner | ||
| * [GitHub repository](https://github.com/KernelTuner/kernel_tuner) | ||
| * [Documentation](https://kerneltuner.github.io/kernel_tuner/stable/) | ||
| * [Tutorial](https://github.com/KernelTuner/kernel_tuner_tutorial) |