Minutes_2021_04_20

Numba Meeting: 2021-04-20

Attendees: Todd, Graham, Guilherme, Hadia, Jim, Siu, Stu, Val

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

An update on target extension/overload work
- target overload is merged
- Graham started to adapt the CUDA target
  - example: https://github.com/numba/numba/pull/6944/files#diff-0d9aaa2fb3ae3cd0a252cc08f5f352ca6c29d40957b964ebf0cb1d3d50720779R62-R66
- Stuart continue to refactor the codebase due to fallout from this work
- targets are now isolated (to some degree)
- import time gone down 40%
Compiler flags propagation
Concern for upcoming release
- With the amount and complexity of work we are doing, we are prioritizing stability before compiler performance. We might see some compiler speed regression in the upcoming release.
slice None vs sys.maxsize
- https://github.com/numba/numba/pull/6939#issuecomment-822656830
- JimP: AwkwardArray picked the choice that maxsize is a magic number. So clamping the space to 2**64 - 2 numbers.
- Stu: Look at CPython unittest for known issues.
- JimP: Sparse container may use up 2**64 and more.
- JimP: without the support for bigint, operating near the limit 2**64 (or intp) is already unlikely.

#6934 - broken link for nrt.h in "notes on numba runtime" page
#6933 - Undocumented behaviour in prange
#6932 - Memory leak when returning bytes from input argument
#6931 - Boxing for slice
#6930 - Inconsistent behavior of reshape between numpy and numba/cuda device array
#6927 - Leading underscore field in structref leads to compilation failure
#6921 - Interop With CuPy's Stream Context Mangers
#6920 - Bad Parfor loop fusion side-effects?
#6919 - CUDA: ffs is off-by-1

#6940 - Fix function resolution for intrinsics across hardware.
#6939 - Implement slice boxing
#6937 - Fix memory leak in bytes boxing
#6936 - CUDA: Implement support for PTDS globally
#6935 - fixes broken link in numba-runtime.rst
#6928 - Add preliminary (limited to at most 3 dimensions) support for axis to argmax
#6926 - [WIP] Keyword args support for Numpy functions when parallel=True option is specified
#6924 - CUDA: Fix ffs