Re-evaluate utility of IaaS
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 18
- Forks
- 28
- Avg merge
- 2d 2h
- Merged PRs (30d)
- 7
Description
The IaaS setup makes sense on LDG, where we have at most 8 GPUs per node and none of any consequence in the condor pool. As we look to do inference on other clusters with more GPUs distributed over multiple nodes (OSG, Delta), it's not clear to me that this setup is still advantageous (particularly for OSG, where communication across nodes doesn't seem possible). We should benchmark throughput with just loading the model in-process.
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
No file or test is named. Start by locating the existing IaaS setup and inference entry point, then benchmark throughput with the model loaded in-process across LDG, OSG, and Delta. Done means results that show whether the current setup remains advantageous.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- distributed-systems, infrastructure, machine-learning
- Issue type
- Refactor
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Quiet
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100