gridfm / gridfm/gridfm-graphkit
normalization and the transform on GPU
Open
Nobody has claimed this yet.
enhancement
- Dominant language
- Python
- Stars
- 105
- Forks
- 36
- Avg merge
- 1d 8h
- Merged PRs (30d)
- 9
Description
Right now it is done on cpu by different workers.
Has a big impact on small graphs where normalization and transform is a big chunk of the total time, and where workers don't have time to prepare the next batches "in the background" when the GPU is busy doing inference.
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 files or tests are named. Start by locating the CPU worker code that performs normalization and transform, then trace the GPU inference path and benchmark small graphs; done means those operations run on the GPU and the reported small-graph performance bottleneck is reduced.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning, performance
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Quiet
- Clarity
- Needs clarification
- Newbie friendliness
- 45/100