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
Uses elementwise interface to generalize canonicalization pattern and add a new
pattern for vector.contract case.
Differential Revision: https://reviews.llvm.org/D104343
Support multi-dimension vector for InsertMap/ExtractMap op and update the
transformations. Currently the relation between IDs and dimension is implicitly
deduced from the types. We can then calculate an AffineMap based on it. In the
future the AffineMap could be part of the operation itself.
Differential Revision: https://reviews.llvm.org/D90995
This revision refactors the way that attributes/types are considered when generating aliases. Instead of considering all of the attributes/types of every operation, we perform a "fake" print step that prints the operations using a dummy printer to collect the attributes and types that would actually be printed during the real process. This removes a lot of attributes/types from consideration that generally won't end up in the final output, e.g. affine map attributes in an `affine.apply`/`affine.for`.
This resolves a long standing TODO w.r.t aliases, and helps to have a much cleaner textual output format. As a datapoint to the latter, as part of this change several tests were identified as testing for the presence of attributes aliases that weren't actually referenced by the custom form of any operation.
To ensure that this wouldn't cause a large degradation in compile time due to the second full print, I benchmarked this change on a very large module with a lot of operations(The file is ~673M/~4.7 million lines long). This file before this change take ~6.9 seconds to print in the custom form, and ~7 seconds after this change. In the custom assembly case, this added an average of a little over ~100 miliseconds to the compile time. This increase was due to the way that argument attributes on functions are structured and how they get printed; i.e. with a better representation the negative impact here can be greatly decreased. When printing in the generic form, this revision had no observable impact on the compile time. This benchmarking leads me to believe that the impact of this change on compile time w.r.t printing is closely related to `print` methods that perform a lot of additional/complex processing outside of the OpAsmPrinter.
Differential Revision: https://reviews.llvm.org/D90512
Fix semantic in the distribute integration test based on offline feedback. This
exposed a bug in block distribution, we need to make sure the id is multiplied
by the stride of the vector. Fix the transformation and unit test.
Differential Revision: https://reviews.llvm.org/D89291
Based on discourse discussion, fix the doc string and remove examples with
wrong semantic. Also fix insert_map semantic by adding missing operand for
vector we are inserting into.
Differential Revision: https://reviews.llvm.org/D89563
When distributing a vector larger than the given multiplicity, we can
distribute it by block where each id gets a chunk of consecutive element
along the dimension distributed. This adds a test for this case and adds extra
checks to make sure we don't distribute for cases not multiple of multiplicity.
Differential Revision: https://reviews.llvm.org/D89061
Add basic canonicalization patterns for the extractMap/insertMap to allow them
to be folded into Transfer ops.
Also mark transferRead as memory read so that it can be removed by dead code.
Differential Revision: https://reviews.llvm.org/D88622
This is the first of several steps to support distributing large vectors. This
adds instructions extract_map and insert_map that allow us to do incremental
lowering. Right now the transformation only apply to simple pointwise operation
with a vector size matching the multiplicity of the IDs used to distribute the
vector.
This can be used to distribute large vectors to loops or SPMD.
Differential Revision: https://reviews.llvm.org/D88341