Context: https://discourse.llvm.org/t/psa-retire-linalg-filter-based-patterns/63785
In the process, also retire `tileConsumerAndFuseProducers` that is now replaced by `tileConsumerAndFuseProducerGreedilyUsingSCFForOp`.
Context: https://discourse.llvm.org/t/psa-retire-tileandfuselinalgops-method/63850
When performing this replacement, a change of behavior appeared: the older `tileConsumerAndFuseProducers` would split the parallel
and non-parallel dimensions automatically and perform a first level of tile-and-fuse on parallel dimensions only and then introduce a
second level of tiling-only on the reduction dimensions. The newer `tileConsumerAndFuseProducerGreedilyUsingSCFForOp` on the other hand
does not perform this breakdown. As a consequence, the transform specification is evolved to produce the same output.
Additionally, replace some uses of `unsigned` by `int64_t` where possible without pulling in larger interface changes (left for a future PR).
Context: https://www.youtube.com/watch?v=Puio5dly9N8
Lastly, tests that were performing tile and fuse and distribute on tensors are retired: the generated IR mixing scf.for, tensors and
distributed processor ids was racy at best ..
Differential Revision: https://reviews.llvm.org/D135559
The patch introduces the required changes to update the pass declarations and definitions to use the new autogenerated files and allow dropping the old infrastructure.
Reviewed By: mehdi_amini, rriddle
Differential Review: https://reviews.llvm.org/D132838
The patch introduces the required changes to update the pass declarations and definitions to use the new autogenerated files and allow dropping the old infrastructure.
Reviewed By: mehdi_amini, rriddle
Differential Review: https://reviews.llvm.org/D132838
Combine the recently added utilities for folded-by-construction affine
operations with the attribute-based Range to enable more folding. This
decreases the amount of emitted code but has little effect on test
precisely because the tests are not checking for the spurious constants.
The difference in the shape of affine maps comes from the internals of
affine folding.
Depends on D129633
Reviewed By: nicolasvasilache
Differential Revision: https://reviews.llvm.org/D130167
While most of methods in ViewLikeInterface accept an `OpFoldResult` for
the offset/size/stride that may be static, represented as `Attribute`,
or dynamic, represented as `Value`, the `Range` abstraction only
accepted `Values`. This can often lead to known-constant
offset/size/strides being materialized into constant operations and
hinder further constant propagation without explicitly running the
constant folding pass. This often leads to a more complicated than
necessary addressing code being emitted. Switch `Range` to use
`OpFoldResult`. Code that uses `Range` currently keeps materializing the
constants to minimize the effect of this change on the IR. Further
commits will make use of this.
Reviewed By: nicolasvasilache, mravishankar
Differential Revision: https://reviews.llvm.org/D129633
In `linalg::tileConsumerAndFuseProducers`, there are two levels of
tiling and fusion; we partition the tile sizes and only use one
half for each of them. The partition is using the first non-parallel
dimension *after* interchange as the boundary. However, concrete
tiling happens *together with* loop interchange, so we still need
to provide the partial tile sizes *before* the interchange.
Otherwise, there will be inconsistency, which is what this patch
is to fix.
Reviewed By: ThomasRaoux
Differential Revision: https://reviews.llvm.org/D129804
The existing implementation of the TilingInterface for Linalg ops was not
modifying the `linalg.index` ops contained within other Linalg ops (they need
to be summed up with the values of respective tile loop induction variables),
which led to the interface-based tiling being incorrect for any Linalg op with
index semantics.
In the process, fix the function performing the index offsetting to use the
pattern rewriter API instead of RAUW as it is being called from patterns and
may mess up the internal state of the rewriter. Also rename the function to
clearly catch all uses.
Depends On D129365
Reviewed By: mravishankar
Differential Revision: https://reviews.llvm.org/D129366
Bubble up extract_slice above Linalg operation.
A sequence of operations
%0 = linalg.<op> ... arg0, arg1, ...
%1 = tensor.extract_slice %0 ...
can be replaced with
%0 = tensor.extract_slice %arg0
%1 = tensor.extract_slice %arg1
%2 = linalg.<op> ... %0, %1, ...
This results in the reduce computation of the linalg operation.
The implementation uses the tiling utility functions. One difference
from the tiling process is that we don't need to insert the checking
code for the out-of-bound accesses. The use of the slice itself
represents that the code writer is sure about the boundary condition.
To avoid adding the boundary condtion check code, `omitPartialTileCheck`
is introduced for the tiling utility functions.
Differential Revision: https://reviews.llvm.org/D122437
This revision introduces a heuristic to stop fusion for shape-only tensors. A shape-only tensor only defines the shape of the consumer computation while the data is not used. Pure producer consumer fusion thus shall not fuse the producer of a shape-only tensor. In particular, since the shape-only tensor will have other uses that actually consume the data.
The revision enables fusion for consumers that have two uses of the same tensor. One as input operand and one as shape-only output operand. In these cases, we want to fuse only the input operand and avoid output fusion via iteration argument.
Reviewed By: hanchung
Differential Revision: https://reviews.llvm.org/D120981
This patch removes an old recursive implementation to lower vector.transpose to extract/insert operations
and replaces it with a iterative approach that leverages newer linearization/delinearization utilities.
The patch should be NFC except by the order in which the extract/insert ops are generated.
Reviewed By: nicolasvasilache
Differential Revision: https://reviews.llvm.org/D121321
Adapt `tileConsumerAndFuseProducers` to return failure if the generated tile loop nest is empty since all tile sizes are zero. Additionally, fix `LinalgTileAndFuseTensorOpsPattern` to return success if the pattern applied successfully.
Reviewed By: mravishankar
Differential Revision: https://reviews.llvm.org/D118878
After removing the range type, Linalg does not define any type. The revision thus consolidates the LinalgOps.h and LinalgTypes.h into a single Linalg.h header. Additionally, LinalgTypes.cpp is renamed to LinalgDialect.cpp to follow the convention adopted by other dialects such as the tensor dialect.
Depends On D115727
Reviewed By: nicolasvasilache
Differential Revision: https://reviews.llvm.org/D115728
Remove the tile and fuse test pass that has been replaced by codegen strategy.
Depends On D114067
Reviewed By: nicolasvasilache
Differential Revision: https://reviews.llvm.org/D114068
Add a pattern to apply the new tile and fuse on tensors method. Integrate the pattern into the CodegenStrategy and use the CodegenStrategy to implement the tests.
Depends On D114012
Reviewed By: nicolasvasilache
Differential Revision: https://reviews.llvm.org/D114067
Tile and fuse failed if the outermost tile loop is a reduction dimension. Add the necessary check to handle outermost reductions and introduce a test case to verify the change.
Reviewed By: nicolasvasilache
Differential Revision: https://reviews.llvm.org/D114012
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
Let the calling pass or pattern replace the uses of the original root operation. Internally, the tileAndFuse still replaces uses and updates operands but only of newly created operations.
Reviewed By: nicolasvasilache
Differential Revision: https://reviews.llvm.org/D110169
If no interchange vector is given initialize it with the identity permutation from 0 to number of loops.
Reviewed By: mravishankar
Differential Revision: https://reviews.llvm.org/D110249
Compute the tiled producer slice dimensions directly starting from the consumer not using the producer at all.
Reviewed By: nicolasvasilache
Differential Revision: https://reviews.llvm.org/D110147
Add a helper method to check if an index vector contains a permutation of its indices. Additionally, refactor applyPermutationToVector to take int64_t.
Reviewed By: nicolasvasilache
Differential Revision: https://reviews.llvm.org/D110135
Add a new version of fusion on tensors that supports the following scenarios:
- support input and output operand fusion
- fuse a producer result passed in via tile loop iteration arguments (update the tile loop iteration arguments)
- supports only linalg operations on tensors
- supports only scf::for
- cannot add an output to the tile loop nest
The LinalgTileAndFuseOnTensors pass tiles the root operation and fuses its producers.
Reviewed By: nicolasvasilache, mravishankar
Differential Revision: https://reviews.llvm.org/D109766
This makes it more explicit what the scope of this pass is. The name
of this pass predates fusion on tensors using tile + fuse, and hence
the confusion.
Differential Revision: https://reviews.llvm.org/D106132
Fusion by linearization should not happen when
- The reshape is expanding and it is a consumer
- The reshape is collapsing and is a producer.
The bug introduced in this logic by some recent refactoring resulted
in a crash.
To enforce this (negetive) use case, add a test that reproduces the
error and verifies the fix.
Differential Revision: https://reviews.llvm.org/D104970
* Split memref.dim into two operations: memref.dim and tensor.dim. Both ops have the same builder interface and op argument names, so that they can be used with templates in patterns that apply to both tensors and memrefs (e.g., some patterns in Linalg).
* Add constant materializer to TensorDialect (needed for folding in affine.apply etc.).
* Remove some MemRefDialect dependencies, make some explicit.
Differential Revision: https://reviews.llvm.org/D105165
Interface patterns are unique in that they get added to every operation that also implements that interface, given that they aren't tied to individual operations. When the same interface pattern gets added to multiple operations (such as the current behavior with Linalg), an reference to each of these patterns is added to every op (meaning that an operation will now have N references to effectively the same pattern). This revision fixes this problematic behavior in Linalg, and can bring upwards of a 25% reduction in compile time in Linalg based workloads.
Differential Revision: https://reviews.llvm.org/D104160
LinalgOps that are all parallel do not use the value of `outs`
tensor. The semantics is that the `outs` tensor is fully
overwritten. Using anything other than `init_tensor` can add false
dependencies between operations, when the use is just for the shape of
the tensor. Adding a canonicalization to always use `init_tensor` in
such cases, breaks this dependence.
Differential Revision: https://reviews.llvm.org/D102561
