sokrypton / sokrypton/ColabFold
running on multiple gpus
Open
Nobody has claimed this yet.
- Dominant language
- Jupyter Notebook
- Stars
- 2.9k
- Forks
- 747
- PR merge metrics
- No merged PRs in 30d
Description
I've a question about using more the a GPU on a workstation o HPC node. I've a node with 4 GPUs, 24 Cores and 125GB of RAM.
I like use all the resource why I like prediced on 40 mil proteins, how can make it?, It is possible?
For protein lenght > 1000 I have that make any update to colab?
Contributor 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.
Research direction
The issue does not name a file, test, or entry point. First clarify whether multi-GPU execution on a four-GPU workstation or HPC node is supported and what changes are needed for sequences longer than 1000 residues. Done would require a documented, reproducible approach for both requests.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- jupyter-notebook
- Domain
- bioinformatics, machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 15/100