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Add GPU Computing section with frameworks, libraries, and tools #25

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Expand Up @@ -17,6 +17,7 @@ High Performance Computing tools and resources for engineers and administrators.
- [Compilers](#compilers)
- [MPI](#mpi)
- [Parallel Computing](#parallel-computing)
- [GPU Computing](#gpu-computing)
- [Benchmarking](#benchmarking)
- [Miscellaneous](#miscellaneous)
- [Performance](#performance)
Expand Down Expand Up @@ -85,6 +86,48 @@ High Performance Computing tools and resources for engineers and administrators.
- [ArrayFire](https://arrayfire.org/docs/index.htm) - A general purpose tensor library that simplifies the process of software development for parallel architectures `other`.
- [OpenMP](https://www.openmp.org/) - OpenMP is an application programming interface that supports multi-platform shared-memory multiprocessing programming `other`.

## GPU Computing
### GPU Programming Frameworks

* [CUDA](https://developer.nvidia.com/cuda-toolkit) - NVIDIA's parallel computing platform and programming model for GPU acceleration `Proprietary`.
* [ROCm](https://rocm.docs.amd.com/) - AMD's open-source software platform for GPU computing supporting HIP, OpenMP, and OpenCL ([Source Code](https://github.com/ROCm/ROCm)) `MIT`.
* [HIP](https://rocm.docs.amd.com/projects/HIP/en/latest/) - Heterogeneous-compute Interface for Portability - portable GPU programming for AMD and NVIDIA ([Source Code](https://github.com/ROCm/HIP)) `MIT`.
* [oneAPI](https://www.intel.com/content/www/us/en/developer/tools/oneapi/overview.html) - Intel's unified programming model for CPUs, GPUs, and accelerators supporting SYCL and DPC++ `Proprietary`.
* [OpenCL](https://www.khronos.org/opencl/) - Open standard for cross-platform parallel programming of heterogeneous systems `Apache-2.0`.
* [SYCL](https://www.khronos.org/sycl/) - High-level C++ abstraction for heterogeneous computing built on OpenCL `Apache-2.0`.
* [Kokkos](https://kokkos.org/) - Performance portable programming model for HPC applications across different architectures ([Source Code](https://github.com/kokkos/kokkos)) `Apache-2.0`.
* [RAJA](https://raja.readthedocs.io/) - Portable abstraction layer for HPC codes supporting CUDA, HIP, OpenMP ([Source Code](https://github.com/LLNL/RAJA)) `BSD-3`.
* [OpenACC](https://www.openacc.org/) - Directive-based programming standard for parallel computing with GPUs and multicore CPUs `other`.


### GPU Libraries

* [cuBLAS](https://developer.nvidia.com/cublas) - NVIDIA's GPU-accelerated BLAS (Basic Linear Algebra Subprograms) library `Proprietary`.
* [cuDNN](https://developer.nvidia.com/cudnn) - NVIDIA's GPU-accelerated library for deep neural networks `Proprietary`.
* [cuFFT](https://developer.nvidia.com/cufft) - NVIDIA's Fast Fourier Transform library for GPUs `Proprietary`.
* [cuSPARSE](https://developer.nvidia.com/cusparse) - NVIDIA's GPU-accelerated library for sparse matrix operations `Proprietary`.
* [rocBLAS](https://rocm.docs.amd.com/projects/rocBLAS/en/latest/) - AMD's GPU-accelerated BLAS implementation ([Source Code](https://github.com/ROCm/rocBLAS)) `MIT`.
* [rocFFT](https://rocm.docs.amd.com/projects/rocFFT/en/latest/) - AMD's Fast Fourier Transform library for GPUs ([Source Code](https://github.com/ROCm/rocFFT)) `MIT`.
* [MIOpen](https://rocm.docs.amd.com/projects/MIOpen/en/latest/) - AMD's library for high-performance machine learning primitives ([Source Code](https://github.com/ROCm/MIOpen)) `MIT`.
* [NCCL](https://developer.nvidia.com/nccl) - NVIDIA Collective Communications Library for multi-GPU communication ([Source Code](https://github.com/NVIDIA/nccl)) `BSD-3`.
* [RCCL](https://rocm.docs.amd.com/projects/rccl/en/latest/) - AMD's collective communications library for multi-GPU ([Source Code](https://github.com/ROCm/rccl)) `MIT`.
* [Thrust](https://thrust.github.io/) - C++ parallel algorithms library built on CUDA ([Source Code](https://github.com/NVIDIA/thrust)) `Apache-2.0`.
* [oneMKL](https://www.intel.com/content/www/us/en/developer/tools/oneapi/onemkl.html) - Intel's oneAPI Math Kernel Library for optimized math routines ([Source Code](https://github.com/oneapi-src/oneMKL)) `Apache-2.0`.


### GPU Tools & Utilities

* [NVIDIA HPC SDK](https://developer.nvidia.com/hpc-sdk) - Comprehensive suite of compilers, libraries and tools for HPC `Proprietary`.
* [nvidia-smi](https://developer.nvidia.com/nvidia-system-management-interface) - NVIDIA System Management Interface for monitoring and managing GPU devices `Proprietary`.
* [rocm-smi](https://rocm.docs.amd.com/projects/rocm_smi_lib/en/latest/) - ROCm System Management Interface for AMD GPUs ([Source Code](https://github.com/ROCm/rocm_smi_lib)) `MIT`.
* [DCGM](https://developer.nvidia.com/dcgm) - NVIDIA Data Center GPU Manager for cluster management ([Source Code](https://github.com/NVIDIA/DCGM)) `Apache-2.0`.
* [HIPIFY](https://rocm.docs.amd.com/projects/HIPIFY/en/latest/) - Tool to convert CUDA code to portable HIP code ([Source Code](https://github.com/ROCm/HIPIFY)) `MIT`.
* [Nsight Systems](https://developer.nvidia.com/nsight-systems) - System-wide performance analysis tool for NVIDIA GPUs `Proprietary`.
* [Nsight Compute](https://developer.nvidia.com/nsight-compute) - Interactive kernel profiler for CUDA applications `Proprietary`.
* [rocprof](https://rocm.docs.amd.com/projects/rocprofiler/en/latest/) - Profiling tool for HIP applications on AMD GPUs ([Source Code](https://github.com/ROCm/rocprofiler)) `MIT`.
* [Intel VTune Profiler](https://www.intel.com/content/www/us/en/developer/tools/oneapi/vtune-profiler.html) - Performance profiler for CPU, GPU, and FPGA `Proprietary`.
* [Omniperf](https://rocm.docs.amd.com/projects/omniperf/en/latest/) - AMD's system performance profiling tool for machine learning/HPC workloads ([Source Code](https://github.com/ROCm/omniperf)) `MIT`.

## Benchmarking
- [OSU Benchmarks](https://mvapich.cse.ohio-state.edu/benchmarks/) - A collection of benchmarking tools for MPI developed by Ohio State University `other`.
- [Intel MPI Benchmarks](https://software.intel.com/content/www/us/en/develop/articles/intel-mpi-benchmarks.html) - A set of benchmarks developed by Intel for use with their Intel MPI `other`.
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