GPU builds of the llama-rpc image (CUDA, Vulkan)
Nobody has claimed this yet.
Assessment
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Newbie friendliness
- 30/100
- Issue type
- Feature
- Clarity
- Mostly clear
- Activity status
- Active
- Tech stack
- docker, github-actions
- Domain
- devops, infrastructure
Research direction
Start with the image build in .github/workflows/llama-rpc.yml, then find where llama-distributed reads the GPU inventory and chooses a worker's variant. Done means CUDA and Vulkan tags are built, the right tag is picked per machine, and GPU workers are marked with "gpu": true. The issue does not say how a worker reports its GPU, so check that first.
Written by the indexing model from the issue text.
Description
ghcr.io/a-hackers-guide/llama-rpc is CPU-only today. Add CUDA and Vulkan variants (tags like b12019-cuda, b12019-vulkan) built in .github/workflows/llama-rpc.yml, and let llama-distributed pick the variant per machine from its GPU inventory. Mark GPU workers with "gpu": true once the image can use them.
- Dominant language
- Go
- Stars
- 1
- Forks
- 0
- Avg merge
- 12m
- Merged PRs (30d)
- 2
Getting set up
- No Dockerfile or Docker Compose file
- No pull request template
- Read the contributing guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
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