gpufort
clang-ocl
| gpufort | clang-ocl | |
|---|---|---|
| 2 | 1 | |
| 158 | 26 | |
| 0.0% | - | |
| 0.0 | 3.4 | |
| 5 months ago | 16 days ago | |
| Fortran | CMake | |
| MIT License | GNU General Public License v3.0 or later |
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gpufort
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(Tutorial) Porting a simple Fortran application to GPUs with HIPFort
There is a gpufort project that provides something a bit more like what you're suggesting, but I'm not sure how useful it is in its current state.
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AI Seamless Texture Generator Built-In to Blender
https://rocmdocs.amd.com/en/latest/Deep_learning/Deep-learni...
RadeonOpenCompute/ROCm_Documentation: https://github.com/RadeonOpenCompute/ROCm_Documentation
ROCm-Developer-Tools/HIPIFYhttps://github.com/ROCm-Developer-Tools/HIPIFY :
> hipify-clang is a clang-based tool for translating CUDA sources into HIP sources. It translates CUDA source into an abstract syntax tree, which is traversed by transformation matchers. After applying all the matchers, the output HIP source is produced.
ROCmSoftwarePlatform/gpufort: https://github.com/ROCmSoftwarePlatform/gpufort :
> GPUFORT: S2S translation tool for CUDA Fortran and Fortran+X in the spirit of hipify
ROCm-Developer-Tools/HIP https://github.com/ROCm-Developer-Tools/HIP:
> HIP is a C++ Runtime API and Kernel Language that allows developers to create portable applications for AMD and NVIDIA GPUs from single source code. [...] Key features include:
> - HIP is very thin and has little or no performance impact over coding directly in CUDA mode.
> - HIP allows coding in a single-source C++ programming language including features such as templates, C++11 lambdas, classes, namespaces, and more.
> - HIP allows developers to use the "best" development environment and tools on each target platform.
> - The [HIPIFY] tools automatically convert source from CUDA to HIP.
> - * Developers can specialize for the platform (CUDA or AMD) to tune for performance or handle tricky cases.*
clang-ocl
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AI Seamless Texture Generator Built-In to Blender
From the Arch wiki, which has a list of GPU runtimes (but not TPU or QPU runtimes) and arch package names: OpenCL, SYCL, ROCm, HIP,: https://wiki.archlinux.org/title/GPGPU :
> GPGPU stands for General-purpose computing on graphics processing units.
- "PyTorch OpenCL Support" https://github.com/pytorch/pytorch/issues/488
- Blender re: removal of OpenCL support in 2021 :
> The combination of the limited Cycles split kernel implementation, driver bugs, and stalled OpenCL standard has made maintenance too difficult. We can only make the kinds of bigger changes we are working on now by starting from a clean slate. We are working with AMD and Intel to get the new kernels working on their GPUs, possibly using different APIs (such as CYCL, HIP, Metal, …).
- https://gitlab.com/illwieckz/i-love-compute
- https://github.com/vosen/ZLUDA
- https://github.com/RadeonOpenCompute/clang-ocl
AMD ROCm: https://en.wikipedia.org/wiki/ROCm
AMD ROcm supports Pytorch, TensorFlow, MlOpen, rocBLAS on NVIDIA and AMD GPUs:
What are some alternatives?
stable_diffusion.openvino
ROCm_Documentation - Legacy ROCm Software Platform Documentation
ZLUDA - CUDA on AMD GPUs
HIP - HIP: C++ Heterogeneous-Compute Interface for Portability
aomp - AOMP is an open source Clang/LLVM based compiler with added support for the OpenMP® API on Radeon™ GPUs. Use this repository for releases, issues, documentation, packaging, and examples.
dream-textures - Stable Diffusion built-in to Blender
CLIP - CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image
stable-diffusion-webui - Stable Diffusion web UI
stable-diffusion - This version of CompVis/stable-diffusion features an interactive command-line script that combines text2img and img2img functionality in a "dream bot" style interface, a WebGUI, and multiple features and other enhancements. [Moved to: https://github.com/invoke-ai/InvokeAI]
i-love-compute