Minutes_2022_11_22
Siu Kwan Lam edited this page Nov 22, 2022
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1 revision
Attendees: Siu Kwan Lam, Todd A. Anderson, Andre Masella, Graham Markall, Guilherme, Ianna Osborne, Mathew Murray, stuart, Kaustubh Chaudhari, brandon willard FPOC (last week): Siu FPOC (incoming): Stuart
NOTE: All communication is subject to the Numba Code of Conduct.
Please refer to this calendar for the next meeting date.
-
math functions redo (Siu/Stu)
- problems:
- untangle incorrect interdependency of
math.*,np.*- e.g. lack of error checking
- different behavior at boundary values betwen
mathvsnumpymath functions.
- different behavior at boundary values betwen
- e.g. lack of error checking
- inconsistent performance e.g. simd-vectorize
- CUDA math funcs directly implemented on CUDA intrinsics
- untangle incorrect interdependency of
- proposed solution:
- implement correctly; i.e. follow cpython or numpy
- performance warning on
mathdue to inability to simd-vectorize - advise users to use
numpyfor simd-vectorize-able code
- TODO: make discourse topic for boarder discussion
- For 0.57
- Ufunc equivalences for math functions
- Adds warnings to suggest people to use the ufunc equivalence function
- No breaking or performance changes until 0.58+
- Stuart don't want to do it in pieces. So, it will be all or nothing.
- Need to add an RFC category in discourse.
- problems:
-
Extension hooks (analysis and lowering).
- Numba has a few extension hooks. These are global dictionaries that maps IR nodes to functions (see:
numba.core.analysis.*_extension_*at global scope). For instance, there was a lowering hook to add custom lowering for custom IR nodes. - The question: Should this be the preferred way of doing this?
- Todd: There are three possibilities:
- what we currently have
- do what we just did for lowering_extensions; i.e Convert into passes
- Stuart: this is possible for all cases. (1) exists because of lack of pass management historically. This is better than inject into global states.
- Could move the analysis etc calls into the IR node types themselves. Disadvantage is spreading all these calls about.
- Examples of these extensions mapping for reference:
numba.core.ir_utils.alias_analysis_extensionsnumba.core.ir_utils.alias_func_extensionsnumba.core.ir_utils.is_pure_extensions
- Stuart Q. Is it acceptable to modify globally the compiler behavior?
- Stuart Q. If possible to modify extension, how guarantee that extensions can work together?
- Is there a compiler that has a plugin architecture?
- GCC has a plugin API, there's a security project that builds plugins for this.
- Doing things like adding new IR nodes is impacting core infrastructure.
- For e.g. OpenMP various offload devices have plugin infrastructure, there's a standard API etc.
- Are there invariants where all the things can agree to "play nicely" and not interfere with each other?
- If Numba IR were more close to MLIR it might make it easier to allow extensions etc. But this sort of design is completely different to what exists at present.
- Is a combination needed of 2 and 3. e.g. usedef analysis is fundamental to the node type.
- Fundamentally, this might not be that pressing an issue, nothing is broken right now but the API is now definitely symmetric. Use this discussion as informative towards making extension points for a compiler toolkit.
- Create issue or RFC to keep track of this information.
- Numba has a few extension hooks. These are global dictionaries that maps IR nodes to functions (see:
-
RFC Mission statement review time.
- Please suggest comments for updates/suggestions for changes by end of November 2022.
- Keep review cadence to 6m
-
When is the "jit" fallback to objmode being removed.
- 2 release after full deprecation
- full deprecation scheduled for 0.57.
- should be possible to create custom target to do this if you really want it still.
- forceobj and looplift will still work if specified.
- #8603 - Input type None is not recognized
- #8607 - getitem(array(float64, 2d, C), UniTuple(array(int64, 1d, C) x 2))
- #8609 - CUDA: register an extension globally
- #8610 - Optional UniTuple gives error depending on the signature
- #8612 - numba for pytorch Tensor for multiple gpus
- #8613 - Raise exception fails with whitespace after function def
- #8615 - "SystemError: initialization of _internal failed without raising an exception"
- #8608 - Dynamic jitclass fails