clang-ocl
i-love-compute
| clang-ocl | i-love-compute | |
|---|---|---|
| 1 | 2 | |
| 26 | - | |
| - | - | |
| 3.4 | - | |
| 18 days ago | - | |
| CMake | ||
| GNU General Public License v3.0 or later | - |
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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.
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:
i-love-compute
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LXC GPU Passthrough with AMD GPU Pro drivers?
Good luck. Regarding amd opencl on linux you can find more resources and install scripts here
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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?
ROCm_Documentation - Legacy ROCm Software Platform Documentation
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
dream-textures - Stable Diffusion built-in to Blender
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]
CLIP - CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image
stable_diffusion.openvino