gpufort
aomp
| gpufort | aomp | |
|---|---|---|
| 2 | 1 | |
| 158 | 181 | |
| 0.0% | 3.9% | |
| 0.0 | 9.8 | |
| 5 months ago | 5 days ago | |
| Fortran | Fortran | |
| MIT License | Apache License 2.0 |
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.
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.*
aomp
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GPU support RDNA3 7900 xtx
AMD engineers have released AOMP compiler support for the new RDNA3 GPU architecture (GFX11). https://www.phoronix.com/news/AMD-AOMP-16.0-1 https://github.com/ROCm-Developer-Tools/aomp/releases/tag/rel_16.0-1 But as there are no released models with that architecture, it is hard to know which models AOMP engineers will "support". After seeing the table above, an educated guess would be a future "Pro" workstation model, based on recent history.
What are some alternatives?
stable_diffusion.openvino
rocFFT - Next generation FFT implementation for ROCm
ZLUDA - CUDA on AMD GPUs
stdgpu - stdgpu: Efficient STL-like Data Structures on the GPU
clang-ocl - OpenCL compilation with clang compiler.
hipfort - Fortran interfaces for ROCm libraries
CLIP - CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image
Full-Stack-Fortran - Fortran to WebAssembly
stable-diffusion-webui - Stable Diffusion web UI
AdaptiveCpp - Implementation of SYCL and C++ standard parallelism for CPUs and GPUs from all vendors: The independent, community-driven compiler for C++-based heterogeneous programming models. Lets applications adapt themselves to all the hardware in the system - even at runtime!
dream-textures - Stable Diffusion built-in to Blender
alpaka - Abstraction Library for Parallel Kernel Acceleration :llama: