HIP-CPU
AdaptiveCpp
HIP-CPU | AdaptiveCpp | |
---|---|---|
5 | 19 | |
104 | 1,040 | |
2.9% | 2.2% | |
7.2 | 9.7 | |
about 1 month ago | 8 days ago | |
C++ | C++ | |
MIT License | BSD 2-clause "Simplified" License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
HIP-CPU
- HIP CPU
- [P] Pure C/C++ port of OpenAI's Whisper
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AMD publishes GPUFORT as Open Source to address CUDA’s dominance
If I'm reading this right, this is Fortran's equivalent of HIP, i.e. a way to (semi-)automatically convert CUDA-based solution to a more backend-independent one so that the same source can be run both on CUDA and ROCm GPUs (and potentially more; e.g. they also have an experimental CPU backend).
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Test Coverage with CUDA
So, I know that you asked about cuda, but this might actually be possible in hip, and you can convert your code to hip relatively easily. The path would be to use the CPU implementation (https://github.com/ROCm-Developer-Tools/HIP-CPU) and then run your code coverage on that.
AdaptiveCpp
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What Every Developer Should Know About GPU Computing
Sapphire Rapids is a CPU.
AMD's primary focus for a GPU software ecosystem these days seems to be implementing CUDA with s/cuda/hip, so AMD directly supports and encourages running GPU software written in CUDA on AMD GPUs.
The only implementation for sycl on AMD GPUs that I can find is a hobby project that apparently is not allowed to use either the 'hip' or 'sycl' names. https://github.com/AdaptiveCpp/AdaptiveCpp
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AMD May Get Across the CUDA Moat
Not natively, but AdaptiveCpp (previously hiSycl, then OpenSycl) has a single source single compiler pass, where they basically store LLVM IR as an intermediate representation.
https://github.com/AdaptiveCpp/AdaptiveCpp/blob/develop/doc/...
Performance penalty was within ew precents, at least according to the paper (figure 9 and 10)
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Offloading standard C++ PSTL to Intel, NVIDIA and AMD GPUs with AdaptiveCpp
AdaptiveCpp (formerly known as hipSYCL) is an independent, open source, clang-based heterogeneous C++ compiler project. I thought some of you might be interested in knowing that we recently added support to offload standard C++ parallel STL algorithms to GPUs from all major vendors. E.g.:
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AMD's HIPRT Working Its Way To Blender With ~25% Faster Rendering
In fact SYCL was initially called hipSYCL because it is based on AMD's ROCm/HIP. AMD had hipSYCL code running on the Frontier supercomputer four years ago at least and continues to support it.
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hipSYCL can now generate a binary that runs on any Intel/NVIDIA/AMD GPU - in a single compiler pass. It is now the first single-pass SYCL compiler, and the first with unified code representation across backends.
Apple Silicon support through Metal is something that is actively discussed in hipSYCL. See https://github.com/illuhad/hipSYCL/issues/864 https://github.com/illuhad/hipSYCL/issues/460 (loooong discussion)
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Bringing Nvidia® and AMD support to oneAPI
But really, the DPC++ part of oneAPI (which is many APIs) is just SYCL + extensions, and there are several other SYCL implementations which have already featured CUDA and Hip (AMD) support for a long time. The most popular and widely-used is hipSYCL, which we've been using in an HPC context on NV hardware for over 4 years now.
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Intel oneAPI 2023 Released - AMD & NVIDIA Plugins Available
Unfortunately, the AMD and Nvidia plugins are proprietary. AMD users are probably better served with hipSYCL, if they somehow find an application using SYCL...
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There is framework for everything.
Also, you might want to take a look at an implementation like hipSYCL :)
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The Next Platform: "Intel Takes The SYCL To Nvidia's CUDA With Migration Tool"
Yup. SYCL is the future: https://github.com/illuhad/hipSYCL
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Phoronix: "Intel's Vulkan Linux Driver Adds Experimental Mesh Shader Support For DG2/Alchemist"
ROCm is completely independent from these. It's a compute stack containing an OpenCL implementation for Radeon GPUs, plus a CUDA-like language called HIP which can be compiled to either device code for Radeon GPUs or to PTX to work with Nvidia GPUs. However, some researchers also created hipSYCL that allows SYCL to run atop HIP; you can think of it like DXVK - the program contains the DirectX/SYCL API, and DXVK/hipSYCL converts it to Vulkan/HIP (with one difference - DXVK does the conversion at runtime, while hipSYCL does it at compile time).
What are some alternatives?
libcudacxx - [ARCHIVED] The C++ Standard Library for your entire system. See https://github.com/NVIDIA/cccl
ROCm - AMD ROCm™ Software - GitHub Home [Moved to: https://github.com/ROCm/ROCm]
rocFFT - Next generation FFT implementation for ROCm
triSYCL - Generic system-wide modern C++ for heterogeneous platforms with SYCL from Khronos Group
HIP - HIP: C++ Heterogeneous-Compute Interface for Portability
stdgpu - stdgpu: Efficient STL-like Data Structures on the GPU
cuda-api-wrappers - Thin C++-flavored header-only wrappers for core CUDA APIs: Runtime, Driver, NVRTC, NVTX.
XNNPACK - High-efficiency floating-point neural network inference operators for mobile, server, and Web
cuda_memtest - Fork of CUDA GPU memtest :eyeglasses:
AITemplate - AITemplate is a Python framework which renders neural network into high performance CUDA/HIP C++ code. Specialized for FP16 TensorCore (NVIDIA GPU) and MatrixCore (AMD GPU) inference.
gpuowl - GPU Mersenne primality test.