SciML / SciML/ParallelParticleSwarms.jl
Benchmarks?
Open
Nobody has claimed this yet.
- Dominant language
- Julia
- Stars
- 30
- Forks
- 4
- Avg merge
- 5h 11m
- Merged PRs (30d)
- 14
Description
- https://github.com/ljvmiranda921/pyswarms (Does not have GPU parallelized implementation IIUC)
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 reviewing the referenced pyswarms project and this repository's existing benchmark entry points; the issue names no files or tests. Define comparable particle-swarm workloads and document benchmark results that clarify whether a GPU-parallelized implementation exists or is needed.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- julia, python
- Domain
- machine-learning, performance
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100