[all-commits] [llvm/llvm-project] 347d59: [mlir][Linalg] Convolution tiling added to ConvOp ...

Jakub Lichman via All-commits all-commits at lists.llvm.org
Thu Sep 17 02:40:29 PDT 2020


  Branch: refs/heads/master
  Home:   https://github.com/llvm/llvm-project
  Commit: 347d59b16c71194d7a9372dd69d3e41ebeca3113
      https://github.com/llvm/llvm-project/commit/347d59b16c71194d7a9372dd69d3e41ebeca3113
  Author: Jakub Lichman <limo at google.com>
  Date:   2020-09-17 (Thu, 17 Sep 2020)

  Changed paths:
    M mlir/include/mlir/Dialect/Linalg/Transforms/Transforms.h
    M mlir/integration_test/Dialect/Linalg/CPU/test-conv-1d-call.mlir
    M mlir/integration_test/Dialect/Linalg/CPU/test-conv-1d-ncw-call.mlir
    M mlir/integration_test/Dialect/Linalg/CPU/test-conv-1d-nwc-call.mlir
    M mlir/integration_test/Dialect/Linalg/CPU/test-conv-2d-call.mlir
    M mlir/integration_test/Dialect/Linalg/CPU/test-conv-2d-nchw-call.mlir
    M mlir/integration_test/Dialect/Linalg/CPU/test-conv-2d-nhwc-call.mlir
    M mlir/integration_test/Dialect/Linalg/CPU/test-conv-3d-call.mlir
    M mlir/integration_test/Dialect/Linalg/CPU/test-conv-3d-ncdhw-call.mlir
    M mlir/integration_test/Dialect/Linalg/CPU/test-conv-3d-ndhwc-call.mlir
    M mlir/lib/Dialect/Linalg/Transforms/Vectorization.cpp
    M mlir/test/Conversion/LinalgToVector/linalg-to-vector.mlir
    M mlir/test/lib/Transforms/TestConvVectorization.cpp

  Log Message:
  -----------
  [mlir][Linalg] Convolution tiling added to ConvOp vectorization pass

ConvOp vectorization supports now only convolutions of static shapes with dimensions
of size either 3(vectorized) or 1(not) as underlying vectors have to be of static
shape as well. In this commit we add support for convolutions of any size as well as
dynamic shapes by leveraging existing matmul infrastructure for tiling of both input
and kernel to sizes accepted by the previous version of ConvOp vectorization.
In the future this pass can be extended to take "tiling mask" as a user input which
will enable vectorization of user specified dimensions.

Differential Revision: https://reviews.llvm.org/D87676




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