Machine Learning SIG
Adam J. Stewart edited this page Mar 23, 2023
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7 revisions
- How to increase industry participation
- AMD/NVIDIA?
- Google/Meta?
- Should we make this group public?
- Introductions
- Progress since last meeting
- PyTorch 2.0: https://github.com/spack/spack/pull/36132
- TF 2.12: https://github.com/spack/spack/pull/36263
- tensorboard-data-server Linux aarch64 support: https://github.com/spack/spack/pull/34437
- Pipelines
- Get PyTorch + ROCm working
- Add tests for Linux aarch64 and ppc64le
- Introductions
- Progress since last meeting
- New JAX package: https://github.com/spack/spack/pull/27849
- New TF versions: https://github.com/spack/spack/pull/31615, https://github.com/spack/spack/pull/32544
- TF ROCm support: https://github.com/spack/spack/pull/32248
- Discussion of progress on overall goals
- Next steps
- ML stack in CI: need help from GitLab folks
- Reach out to Google/Meta to ask about maintainers and build support
- Reach out to Tamara to ask about distributed/parallel testing in
spack test - Ask about scientific Python software stack (spider, jupyter, matplotlib, etc.)
- Concerted effort to fix TF/protobuf linking issues
- Concerted effort to fix TF build on macOS (x86_64 first, then arm64)
- Introductions
- Discussion of overall goals of this SIG
- How to organize this SIG?
- Mostly relying on GitHub Projects to track progress
- Anyone can volunteer/assign themselves to work on a task
- Communications over GitHub/Slack preferred, email used until we can get everyone on Slack
- How to advertise this SIG?
- Would love industry partnerships to help maintain build recipes
- Need some kind of incentive: faster benchmarks?
- Ideally, every ML package will have both a Spack developer and a ML library developer willing to maintain that build recipe
- Discussion of next steps moving forward
- Need to decide what exactly we are willing to maintain
- Which packages?
- Which platforms?
- Which versions?
- Idea: only maintain the packages/platforms/versions we test in CI
- Scope: only ML packages, not generic data analysis (numpy, pandas) or visualization (matplotlib) tools
- Need to decide what exactly we are willing to maintain
- Specific PRs in progress that need reviewing
- Update TF/Keras: https://github.com/spack/spack/pull/31615
- ML stack in CI: https://github.com/spack/spack/pull/31592
- New JAX package: https://github.com/spack/spack/pull/27849