ROCm-docker
chipStar
| ROCm-docker | chipStar | |
|---|---|---|
| 3 | 4 | |
| 392 | 147 | |
| 1.0% | 4.8% | |
| 5.1 | 9.7 | |
| 24 days ago | 3 days ago | |
| Shell | C++ | |
| MIT License | GNU General Public License v3.0 or later |
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-docker
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AMD Funded a Drop-In CUDA Implementation Built on ROCm: It's Open-Source
https://rocm.docs.amd.com/projects/install-on-linux/en/lates... links to ROCm/ROCm-docker: https://github.com/ROCm/ROCm-docker which is the source of docker.io/rocm/rocm-terminal: https://hub.docker.com/r/rocm/rocm-terminal :
docker run -it --device=/dev/kfd --device=/dev/dri --group-add video rocm/rocm-terminal -
Stable Diffusion PR optimizes VRAM, generate 576x1280 images with 6 GB VRAM
Not sure about the 6600, but there is a guide for Linux at least:
https://m.youtube.com/watch?v=d_CgaHyA_n4&feature=emb_logo
And this is somehow relevant (possibly), as I kept the link open.
https://github.com/RadeonOpenCompute/ROCm-docker/issues/38
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It's working perfectly under Linux
As for the Docker image, I suppose you could compile the image (https://hub.docker.com/r/rocm/pytorch) by yourself using the sources (https://github.com/RadeonOpenCompute/ROCm-docker#building-images), which seems to be quite a bit of work. Better, you could just use an older tag of the upstream image, eg. rocm4.1.1_ubuntu18.04_py3.6_pytorch instead of rocm4.2_ubuntu18.04_py3.6_caffe2 or latest . Just make sure your container version matches your host ROCm version.
chipStar
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AMD Funded a Drop-In CUDA Implementation Built on ROCm: It's Open-Source
There is already a work-in-progress implementation of HIP on top of OpenCL https://github.com/CHIP-SPV/chipStar and the Mesa RustiCL folks are quite interested in getting that to run on top of Vulkan.
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Vcc – The Vulkan Clang Compiler
chipStar (formerly CHIP-SPV) might also be worth checking out: https://github.com/CHIP-SPV/chipStar
It compiles CUDA/HIP C++ to SPIR-V that can run on top of OpenCL or Level Zero. (It does require OpenCL's compute flavored SPIR-V, instead of graphics flavored SPIR-V as seen in OpenGL or Vulkan. I also think it requires some OpenCL extensions that are currently exclusive to Intel NEO, but should on paper be coming to Mesa's rusticl implementation too.
- ChipStar: Run CUDA/Hip on SPIR-V via OpenCL/Level Zero
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In the next 5 years, what do you think can push OpenCL adoption?
Regarding the second item (CUDA to OpenCL), have a look at hipstar: https://github.com/CHIP-SPV/hipstar
What are some alternatives?
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FluidX3D - The fastest and most memory efficient lattice Boltzmann CFD software, running on all GPUs via OpenCL.
AiDungeon2-Docker-ROCm - Runs an AIDungeon2 fork in Docker on AMD ROCm hardware.
OpenCL-Wrapper - OpenCL is the most powerful programming language ever created. Yet the OpenCL C++ bindings are cumbersome and the code overhead prevents many people from getting started. I created this lightweight OpenCL-Wrapper to greatly simplify OpenCL software development with C++ while keeping functionality and performance.
ZLUDA - CUDA on AMD GPUs
Cgml - GPU-targeted vendor-agnostic AI library for Windows, and Mistral model implementation.
stable-diffusion - Go to lstein/stable-diffusion for all the best stuff and a stable release. This repository is my testing ground and it's very likely that I've done something that will break it.
hipDNN - A thin wrapper around miOpen and cuDNN
docker-elk - The Elastic stack (ELK) powered by Docker and Compose.
llvm - Intel staging area for llvm.org contribution. Home for Intel LLVM-based projects.
Dokku - A docker-powered PaaS that helps you build and manage the lifecycle of applications
Docker-OSX - Run macOS VM in a Docker! Run near native OSX-KVM in Docker! X11 Forwarding! CI/CD for OS X Security Research! Docker mac Containers.