Differential Revision: https://reviews.llvm.org/D101861

While we figure out how to best add Standard support for scalable
vectors, these instructions provide a workaround for basic arithmetic
between scalable vectors.

Reviewed By: nicolasvasilache

Differential Revision: https://reviews.llvm.org/D100837

Differential Revision: https://reviews.llvm.org/D101798

This revision migrates more code from Linalg into the new permanent home of
SparseTensor. It replaces the test passes with proper compiler passes.

NOTE: the actual removal of the last glue and clutter in Linalg will follow

Reviewed By: bixia

Differential Revision: https://reviews.llvm.org/D101811

We weren't properly visiting region successors when the terminator wasn't return like, which could create incorrect results in the analysis. This revision ensures that we properly visit region successors, to avoid optimistically assuming a value is constant when it isn't.

Differential Revision: https://reviews.llvm.org/D101783

All linalg.init operations must be fed into a linalg operation before
subtensor. The inserted linalg.fill guarantees it executes correctly.

Reviewed By: mravishankar

Differential Revision: https://reviews.llvm.org/D101848

See: https://reviews.llvm.org/D101710

Differential Revision: https://reviews.llvm.org/D101801

Differential Revision: https://reviews.llvm.org/D101710

Ensure the index operations are lowered on all linalg loop lowering paths.

Differential Revision: https://reviews.llvm.org/D101827

Differential Revision: https://reviews.llvm.org/D96776

TransferReadOps that are a scalar read + broadcast are handled by TransferReadToVectorLoadLowering.

Differential Revision: https://reviews.llvm.org/D101808

Lowerings equal and arithmetic_right_shift for elementwise ops to linalg dialect using linalg.generic

Reviewed By: rsuderman

Differential Revision: https://reviews.llvm.org/D101804

This fixes a performance regression in vec-mat vectorization

Reviewed By: asaadaldien

Differential Revision: https://reviews.llvm.org/D101795

This approximation matches the one in Eigen.

```
name                      old cpu/op  new cpu/op  delta
BM_mlir_Log1p_f32/10      83.2ns ± 7%  34.8ns ± 5%  -58.19%    (p=0.000 n=84+71)
BM_mlir_Log1p_f32/100      664ns ± 4%   129ns ± 4%  -80.57%    (p=0.000 n=82+82)
BM_mlir_Log1p_f32/1k      6.75µs ± 4%  0.81µs ± 3%  -88.07%    (p=0.000 n=88+79)
BM_mlir_Log1p_f32/10k     76.5µs ± 3%   7.8µs ± 4%  -89.84%    (p=0.000 n=80+80)
BM_eigen_s_Log1p_f32/10   70.1ns ±14%  72.6ns ±14%   +3.49%  (p=0.000 n=116+112)
BM_eigen_s_Log1p_f32/100   706ns ± 9%   717ns ± 3%   +1.60%   (p=0.018 n=117+80)
BM_eigen_s_Log1p_f32/1k   8.26µs ± 1%  8.26µs ± 1%     ~       (p=0.567 n=84+86)
BM_eigen_s_Log1p_f32/10k  92.1µs ± 5%  92.6µs ± 6%   +0.60%  (p=0.047 n=115+115)
BM_eigen_v_Log1p_f32/10   31.8ns ±24%  34.9ns ±17%   +9.72%    (p=0.000 n=98+96)
BM_eigen_v_Log1p_f32/100   169ns ±10%   177ns ± 5%   +4.66%   (p=0.000 n=119+81)
BM_eigen_v_Log1p_f32/1k   1.42µs ± 4%  1.46µs ± 8%   +2.70%   (p=0.000 n=93+113)
BM_eigen_v_Log1p_f32/10k  14.4µs ± 5%  14.9µs ± 8%   +3.61%  (p=0.000 n=115+110)
```

Reviewed By: ezhulenev, ftynse

Differential Revision: https://reviews.llvm.org/D101765

Given the source and destination shapes, if they are static, or if the
expanded/collapsed dimensions are unit-extent, it is possible to
compute the reassociation maps that can be used to reshape one type
into another. Add a utility method to return the reassociation maps
when possible.

This utility function can be used to fuse a sequence of reshape ops,
given the type of the source of the producer and the final result
type. This pattern supercedes a more constrained folding pattern added
to DropUnitDims pass.

Differential Revision: https://reviews.llvm.org/D101343

Convert subtensor and subtensor_insert operations to use their
rank-reduced versions to drop unit dimensions.

Differential Revision: https://reviews.llvm.org/D101495

The current implementation had a bug as it was relying on the target vector
dimension sizes to calculate where to insert broadcast. If several dimensions
have the same size we may insert the broadcast on the wrong dimension. The
correct broadcast cannot be inferred from the type of the source and
destination vector.

Instead when we want to extend transfer ops we calculate an "inverse" map to the
projected permutation and insert broadcast in place of the projected dimensions.

Differential Revision: https://reviews.llvm.org/D101738

Differential Revision: https://reviews.llvm.org/D101771

Add dedicated pass `convert-linalg-tiled-loops-to-scf` to lower
`linalg.tiled_loop`s.

Differential Revision: https://reviews.llvm.org/D101768

* NFC but has some fixes for CMake glitches discovered along the way (things not cleaning properly, co-mingled depends).
* Includes previously unsubmitted fix in D98681 and a TODO to fix it more appropriately in a smaller followup.

Differential Revision: https://reviews.llvm.org/D101493

Differential Revision: https://reviews.llvm.org/D101511

Differential Revision: https://reviews.llvm.org/D101637

Differential Revision: https://reviews.llvm.org/D101643

The converter assumed that all operands have the same type, that's not
true for select.

Differential Revision: https://reviews.llvm.org/D101767

Move TransposeOp lowering in its own populate function as in some cases
it is better to keep it during ContractOp lowering to better
canonicalize it rather than emiting scalar insert/extract.

Differential Revision: https://reviews.llvm.org/D101647

* This makes them consistent with custom types/attributes, whose constructors will do a type checked conversion. Of course, the base classes can represent everything so never error.
* More importantly, this makes it possible to subclass Type and Attribute out of tree in sensible ways.

Differential Revision: https://reviews.llvm.org/D101734

Differential Revision: https://reviews.llvm.org/D101747

Differential Revision: https://reviews.llvm.org/D101705

Differential Revision: https://reviews.llvm.org/D101535

1) Canonicalize IndexCast(SExt(x)) => IndexCast(x)
2) Provide constant folds of sign_extend and truncate

Differential Revision: https://reviews.llvm.org/D101714

Added canonicalization for vector_load and vector_store. An existing
pattern SimplifyAffineOp can be reused to compose maps that supplies
result into them. Added AffineVectorStoreOp and AffineVectorLoadOp
into static_assert of SimplifyAffineOp to allow operation to use it.

This fixes the bug filed: https://bugs.llvm.org/show_bug.cgi?id=50058

Reviewed By: bondhugula

Differential Revision: https://reviews.llvm.org/D101691

Don't get RegionKindInterface if we won't use it. Noticed by inspection.

(1) migrates the encoding from TensorDialect into the new SparseTensorDialect
(2) replaces dictionary-based storage and builders with struct-like data

Reviewed By: mehdi_amini

Differential Revision: https://reviews.llvm.org/D101669

Stop using the compatibility spellings of `OF_{None,Text,Append}`
left behind by 1f67a3cb. A follow-up
will remove them.

Differential Revision: https://reviews.llvm.org/D101650

Three patterns are added to convert into vector.multi_reduction into a
sequence of vector.reduction as the following:

- Transpose the inputs so inner most dimensions are always reduction.
- Reduce rank of vector.multi_reduction into 2d with inner most
reduction dim (get the 2d canical form)
- 2D canonical form is converted into a sequence of vector.reduction.

There are two things we might worth in a follow up diff:

- An scf.for (maybe optionally) around vector.reduction instead of unrolling it.
- Breakdown the vector.reduction into a sequence of vector.reduction
(e.g tree-based reduction) instead of relying on how downstream dialects
handle it.
  Note: this will requires passing target-vector-length

Differential Revision: https://reviews.llvm.org/D101570

This is the very first step toward removing the glue and clutter from linalg and
replace it with proper sparse tensor types. This revision migrates the LinalgSparseOps
into SparseTensorOps of a sparse tensor dialect. This also provides a new home for
sparse tensor related transformation.

NOTE: the actual replacement with sparse tensor types (and removal of linalg glue/clutter)
will follow but I am trying to keep the amount of changes per revision manageable.

Differential Revision: https://reviews.llvm.org/D101573

Constant-0 dim expr values should be avoided for linalg as it can prevent
fusion. This includes adding support for rank-0 reshapes.

Differential Revision: https://reviews.llvm.org/D101418

This reverts commit a6d92a97.

The build with -DBUILD_SHARED_LIBS=ON is broken.