ROCm_Documentation
i-love-compute
| ROCm_Documentation | i-love-compute | |
|---|---|---|
| 2 | 2 | |
| 108 | - | |
| - | - | |
| 2.8 | - | |
| 11 months ago | - | |
| CSS | ||
| - | - |
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.
ROCm_Documentation
-
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.*
- Why is ROCm still such a dog's breakfast?
i-love-compute
-
LXC GPU Passthrough with AMD GPU Pro drivers?
Good luck. Regarding amd opencl on linux you can find more resources and install scripts here
-
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?
clang-ocl - OpenCL compilation with clang compiler.
HIP - HIP: C++ Heterogeneous-Compute Interface for Portability
gpufort - GPUFORT: S2S translation tool for CUDA Fortran and Fortran+X in the spirit of hipify
HIPIFY - HIPIFY: Convert CUDA to Portable C++ Code [Moved to: https://github.com/ROCm/HIPIFY]
ZLUDA - CUDA on AMD GPUs
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]
stable_diffusion.openvino
CLIP-Mesh - Official implementation of CLIP-Mesh: Generating textured meshes from text using pretrained image-text models
dream-textures - Stable Diffusion built-in to Blender