Minutes_2021_05_04

Numba Meeting: 2021-05-04

Attendees: Brandon, ToddA, Val, Stuart, Siu,

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

0. Feature Discussion/admin

• General updates:

  • vendored cloudpickle 1.6.0
  • refactor of hardware target API
  • ROCm unmaintained status
    • Reasons:
      • Difficulty to port to the new target extension API
      • Current code only works with ROCm v2 series but latest is v4.
      • Lack of active users
      • Lack of testing hardware for newer ROCm HW
    • Will create a new repo to document the above
  • No compilation on import
    • Faster import time!
    • No sideeffect on import

• NumPy subclassing discussion

  • Type-based

  example 1: Todd's PR proposal

  @allocator(MyType)
  def impl():  # need a target
      ...  

  example 2: using @overload + target

  @overload(allocate, target="mygpu")
  def ol_allocate(size):  # need a type
      ...

  example 3: as the (class)method of the Type

  @intrinsic(target="mygpu")
  def intrinsic_allocate(tyctx, size):
      # can get the target
      # get a sig
      def impl(cgctx, builder, args, llargs):
          ... stuff
      return sig, impl
      
  @overload_method(MyType, "allocate", target="mygpu")
  def ol_allocate(): 
      
      def impl():
          intrisic_allocate()
      return impl
      
  @jit
  def foo():
      MyTypeInst.allocate(sz)

  example 4: allocator on target context

  @intrinsic(target="mygpu")
  def allocate(tyctx, size):
      def impl(cgctx, <stuff>):
          cgctx.allocate()
      return impl

  Question. Can it be guaranteed that for a given hardware for a given type there is a single allocator.

  Resolution:

  • Example 3 is needed
  • @overload_classmethod is needed
  • to determine how challenging it is, we may need to adopt example 1 temporarily.

• Dicussion on https://github.com/numba/numba/pull/6996

• Minimum 4 weeks away from current release. Reminder for folks to submit large PR soon to make it into the release.

1. New Issues

• #6984 - AttributeError: 'Array' object has no attribute 'shape'
• #6980 - jax.ndarray.shape not working in @njit with error `unknown attribute shape of readonly buffer
  • Probably best to suggest to do what options exist
• #6979 - LLVM IR parsing error when np.bool_ used inside a closure
  • Lot's of debugging with an eventual very short fix, PR avail

Closed Issues

2. New PRs

• #6991 - Move ROCm target status to "unmaintained".
• #6990 - Refactor hardware extension API to refer to "target" instead.
• #6989 - update threading docs for function loading
• #6988 - Refactor fold_arguments and add typing
• #6987 - Implement int64() cast and __hash__ for datetime-like types.
• #6986 - document release checklist
• #6985 - Implement static set/get items on records with integer index
• #6983 - Support Optional types in ufuncs.
• #6981 - Fix LLVM IR parsing error on use of np.bool_ in globals

Closed PRs

• #6982 - [DO NOT MERGE] Enh/cloudpickle hack
• #6978 - Implement operator.contains for empty Tuples
• #6977 - Vendor cloudpickle

3. Next Release: Version 0.54.0/0.37.0, RC=June 2021