sokrypton / sokrypton/ColabFold
Extremely slow `expandaln` step in `colabfold_search`
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- Jupyter Notebook
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Description
Expected Behavior
colabfold_search executes for 10 sequences on the hours timescale
Current Behavior
colabfold_search for 10 sequences essentially hangs on expandaln (very slow progress bar, it will take 24 hours at this rate)
Note I am running it with 40 threads
Steps to Reproduce (for bugs)
I setup the databases locally without and index.
I had originally tried doing it with an index and db-load-mode 0 since I have NVMe storage. This completely hangs on the first prefiltering step and makes no progress. I thought maybe it had to do with limitations of the node I am on on my HPC cluster (104 cores, 200 GB)
I only have access to nodes with a max of 750 GB RAM, so I don't think in memory index is an option
Is this speed expected given I am indexing on the fly? If not, how can I optimize the speed without in memory index?
Thanks for your time and work.
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
Start by reproducing colabfold_search for 10 sequences with 40 threads and a locally installed database without an index. Compare the expandaln behavior with an index and with db-load-mode 0; done means establishing whether the runtime is expected and identifying a supported optimization path for nodes limited to 750 GB RAM.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- jupyter-notebook
- Domain
- bioinformatics, cli, performance
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 30/100