Speed up cupy with custom kernels
Nobody has claimed this yet.
Assessment
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Newbie friendliness
- 42/100
- Issue type
- Refactor
- Clarity
- Mostly clear
- Activity status
- Stale
- Tech stack
- python
- Domain
- performance
Research direction
Start with src/rapids_singlecell/preprocessing/_kernels/_mean_var_kernel.py and src/rapids_singlecell/preprocessing/_kernels/_sparse2dense.py, then compare the current kernels with the CuPy support introduced in #51. Done means the sum, mean_var, and related operations are faster with the custom kernels.
Written by the indexing model from the issue text.
Description
- Dominant language
- Python
- Stars
- 15
- Forks
- 5
- Avg merge
- 10h 33m
- Merged PRs (30d)
- 9
Contributor guide
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