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[mlir][vector] Add scalable vectors to tests for vector.contract #70039

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banach-space
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@banach-space banach-space commented Oct 24, 2023

Update the remaining tests for matrix multiplication (matmul) in:

  • vector-contract-to-outerproduct-transforms.mlir

with cases for scalable vectors.

Note that in order for the "vector.contract -> vector.outerproduct"
patterns to work, only the non-reduction dimension can be scalable (*).
For Matmul operations that is set to be the N dimension (i.e. rows of
the output matrix), which matches how matrix multiplication are normally
implemented for e.g. Arm's SVE. However, making the M dimension scalable
(i.e. columns of the output matrix) should work as well.

Making both parellel dimensions scalable is left as a TODO for when
support for 2-D scalable vectors is more established (this is
work-in-progress as part of the effort to support Arm's SME in MLIR).

The change in:

  • UnrolledOuterProductGenerator

is a "bug fix" to make sure that the conversion pattern correctly
propagates scalability when creating arith.extf operations.

(*) The conversion tested in this file unrolls along the reduction
dimension, which is not supported for scalable vectors.

@banach-space banach-space changed the title andrzej/extend vec cont to op tests [mlir][vector] Add scalable vectors to tests for vector.contract Oct 24, 2023
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NOTE: Only review the last commit. Other commits are dependencies.

@banach-space banach-space force-pushed the andrzej/extend_vec_cont_to_op_tests branch from b5f879a to 065af62 Compare October 26, 2023 12:15
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These LGTM, thanks!

@banach-space banach-space force-pushed the andrzej/extend_vec_cont_to_op_tests branch 2 times, most recently from 3f8efb7 to 92bd07f Compare October 27, 2023 08:28
Update the remaining tests for matrix multiplication (_matmul_) in:

  * vector-contract-to-outerproduct-transforms.mlir

with cases for scalable vectors.

Note that in order for the "vector.contract -> vector.outerproduct"
patterns to work, only the non-reduction dimension can be scalable (*).
For Matmul operations that is set to be the N dimension (i.e. rows of
the output matrix), which matches how matrix multiplication are normally
implemented for e.g. Arm's SVE. However, making the M dimension scalable
(i.e. columns of the output matrix) should work as well.

Making both parellel dimensions scalable is left as a TODO for when
support for 2-D scalable vectors is more established (this is
work-in-progress as part of the effort to support Arm's SME in MLIR).

The change in:

  * `UnrolledOuterProductGenerator`

is a "bug fix" to make sure that the conversion pattern correctly
propagates scalability when creating `arith.extf` operations.

(*) The conversion tested in this file unrolls along the reduction
dimension, which is not supported for scalable vectors.
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3 participants