This pattern is useful for SPIR-V to unroll to a supported vector size
before later lowerings. The unrolling pattern is closer to an
elementwise op than the transfer ops because the index values from which
to extract elements are captured by the index vector and thus there is
no need to update the base offsets when unrolling gather.
Differential Revision: https://reviews.llvm.org/D149066
Fixed issue with vector.contract default unroll permutation.
Adds support for vector unroll transformations to unroll in different
orders. For example, the vector.contract can be unrolled into a
smaller set of contractions. There is a choice of how to unroll the
decomposition based on the traversal order of (dim0, dim1, dim2).
The choice of traversal order can now be specified by a callback which
given by the caller of the transform. For now, only the
vector.contract, vector.transfer_read/transfer_write operations
support the callback.
Differential Revision: https://reviews.llvm.org/D127004
Reverts commit 1469ebf8382107e0344173f362b690d19e24029d (original commit)
Reverts commit a392a39f75af586e3d3cd046a8361939277e067f (build fix for above commit)
The commit broke tests in out-of-tree projects, indicating that some logical
error was made in the previous change but not covered by current tests.
Adds supprot for vector unroll transformations to unroll in different
orders. For example, the `vector.contract` can be unrolled into a
smaller set of contractions. There is a choice of how to unroll the
decomposition based on the traversal order of (dim0, dim1, dim2).
The choice of traversal order can now be specified by a callback which
given by the caller of the transform. For now, only the
`vector.contract`, `vector.transfer_read/transfer_write` operations
support the callback.
Differential Revision: https://reviews.llvm.org/D127004
Precursor: https://reviews.llvm.org/D110200
Removed redundant ops from the standard dialect that were moved to the
`arith` or `math` dialects.
Renamed all instances of operations in the codebase and in tests.
Reviewed By: rriddle, jpienaar
Differential Revision: https://reviews.llvm.org/D110797
Simplify vector unrolling pattern to be more aligned with rest of the
patterns and be closer to vector distribution.
The new implementation uses ExtractStridedSlice/InsertStridedSlice
instead of the Tuple ops. After this change the ops based on Tuple don't
have any more used so they can be removed.
This allows removing signifcant amount of dead code and will allow
extending the unrolling code going forward.
Differential Revision: https://reviews.llvm.org/D105381
Move the existing optimization for transfer op on tensor to folder and
canonicalization. This handles the write after write case and read after write
and also add write after read case.
Differential Revision: https://reviews.llvm.org/D100597
This reverts commit b5d9a3c92358349d5444ab28de8ab5b2bee33a01.
The commit introduced a memory error in canonicalization/operation
walking that is exposed when compiled with ASAN. It leads to crashes in
some "release" configurations.
Two changes:
1) Change the canonicalizer to walk the function in top-down order instead of
bottom-up order. This composes well with the "top down" nature of constant
folding and simplification, reducing iterations and re-evaluation of ops in
simple cases.
2) Explicitly enter existing constants into the OperationFolder table before
canonicalizing. Previously we would "constant fold" them and rematerialize
them, wastefully recreating a bunch fo constants, which lead to pointless
memory traffic.
Both changes together provide a 33% speedup for canonicalize on some mid-size
CIRCT examples.
One artifact of this change is that the constants generated in normal pattern
application get inserted at the top of the function as the patterns are applied.
Because of this, we get "inverted" constants more often, which is an aethetic
change to the IR but does permute some testcases.
Differential Revision: https://reviews.llvm.org/D98609
Adding unroll support for transfer read and transfer write operation. This
allows to pick the ideal size for the memory access for a given target.
Differential Revision: https://reviews.llvm.org/D89289
