Minutes_2022_11_15

Numba Meeting: 2022-11-15

Attendees: Val, Graham Markall, Ianna Osborne, Jim Pivarski, Matthew Murray, Shannon Quinn, Todd A. Anderson, Siu Kwan Lam, Luk, Andre Masella, stuart, FPOC (last week): Andre FPOC (incoming): Siu

NOTE: All communication is subject to the Numba Code of Conduct.

Please refer to this calendar for the next meeting date.

0. Discussion

• [Done in triage] review dynamic exception PR: https://github.com/numba/numba/pull/8134
• #8525 (stuart)
  • specifically, thoughts on whether the Data-Model Manager (DMMs) should be target based and if a 'generic' target DMM should exist.
  • There's only one DMM and for historical reasons it's only been for CPU.
  • The current patch tests out the idea of chaining a new DMM for a specific target on top of the CPU one for CUDA.
  • In reality, are they mostly generic? Probably... yes.
  • Is there going to be an issue with e.g. float16 between ARM (aarch64) and x86?
    • Maybe the differences are handled at the LLVM level already (on newer LLVMs).
  • Conclusion is to try out this idea/patch on a separate PR. There are concerns about model registration and how to handle that on a per target basis, is some new API needed as part of the target extension API to help with that?
• #8493 (stuart)
  • specifically thoughts on the re-export of numba.core.extending API with partial over some specific target.
    • Comments on whether to re-export or be explicit about the target.
    • Siu: in favour of being explicit (others are in favour too).
• Should we start moving to have numba.cpu for stuff which is just CPU? (stuart)
  • core for generic compiler stuff
  • cpu for cpu specific; e.g. libm math apis
  • nrt could one day work for non-cpu; so are many things in core that can become more generic
  • a lot of numpy.linalg support shouldn't be in core
  • core has too much code. hard to find things
  • Conclusion:
    • Stuart to start putting new math lib code into cpu, cuda, subpackage
• np.ma support (stuart)
  • asking if anyone has use for it. known to be needed in climate science. there's a recent request for its support.
  • interesting challenges in implementation of masked array
    • getitem to handle mask
    • other ndarray operation should be able to work with minimal changes
  • interesting as a validation to Numba's ability make array subtypes and reuse code
  • Luk: targeting arrow. arrow uses mask
  • Siu: Is Arrow a better choice for masked-array like support for the future?
  • Graham: CUDA array interface as a place for describing masking.
• Cache invalidation PR (#8396) update (Luk)
  • PR is ready!
  • Supported:
    • normal dispatchers, overloads, cfuncs, ufuncs
  • Limitations
    • lowlevel API, functions with inline='always', guvectorize, anything involving Parfors.
  • Stuart: Limitations are clear and easy to explain
  • Luk: invalidation behavior is on the safe sound. Moved files will be invalidated.
  • Stuart: dealing with one hard problem at a time is a good approach. Handling potential moves of the packages files that invalidate the cache can be handled at a later time.

New "Ready for Review" PRs

• #8558: [Unicode] support int(str, base=10)

1. New Issues

• #8586 - np.kron behaves differently when compiled with numba
• #8589 - Deal with masked array
• #8591 - performance issue with F-order array
• #8596 - Classes with __enter__ and __exit__ methods, and jitclass decorator can't be used as context managers.
• #8599 - Numba event mechanism is recording seconds as microseconds?

Closed Issues

• #8584 - Cannot import Numba Android ARM64 Termux

2. New PRs

• #8585 - migrate cmath.exp to use overload
• #8590 - Py3.11 support continues
• #8594 - Fix various CUDA lineinfo
• llvmlite#890 - [CI Testing Only] Testing/pr830

Closed PRs

• merged - #8587 - Remove unused refcount removal code, clean core/cpu.py module.
• merged - #8588 - Remove lowering extension hooks, replace with pass infrastructure.
• merged - #8592 - fix failure of test_cache_invalidate due to read-only install
• merged - #8593 - Adjusted ULP precesion for noncentral distribution test
• #8595 - [CI Testing Only] Py3.11ci
• merged - #8597 - Prevent use of NumPy's MaskedArray.
• merged - #8598 - Setup Azure CI to test py3.11

3. Next Release: Version 0.57.0/0.40.0, RC Jan 2023