This commit augments spv.CopyMemory's implementation to support 2 memory
access operands. Hence, more closely following the spec. The following
changes are introduces:
- Customize logic for spv.CopyMemory serialization and deserialization.
- Add 2 additional attributes for source memory access operand.
Reviewed By: antiagainst
Differential Revision: https://reviews.llvm.org/D82710
More efficient implementation of the multiply-reduce pair,
no need to add in a zero vector. Microbenchmarking on AVX2
yields the following difference in vector.contract speedup
(over strict-order scalar reduction).
SPEEDUP SIMD-fma SIMD-mul
4x4 1.45 2.00
8x8 1.40 1.90
32x32 5.32 5.80
Reviewed By: ftynse
Differential Revision: https://reviews.llvm.org/D82833
`llvm.mlir.constant` was originally introduced as an LLVM dialect counterpart
to `std.constant`. As such, it was supporting "function pointer" constants
derived from the symbol name. This is different from `std.constant` that allows
for creation of a "function" constant since MLIR, unlike LLVM IR, supports
this. Later, `llvm.mlir.addressof` was introduced as an Op that obtains a
constant pointer to a global in the LLVM dialect. It naturally extends to
functions (in LLVM IR, functions are globals) and should be used for defining
"function pointer" values instead.
Fixes PR46344.
Differential Revision: https://reviews.llvm.org/D82667
This test largely predates MLIR testing guidelines. Update it to match the
guidelines. In particular, avoid pattern-matching SSA value names, avoid
unnecessary CHECK-NEXT, relax assumptions about the form of SSA names.
Value-returning operations are still matched agaist _any_ name in order to
check that the operation indeed produces values.
Differential Revision: https://reviews.llvm.org/D82656
Add a pass to rewrite sequential chains of `spirv::CompositeInsert`
operations into `spirv::CompositeConstruct` operations.
Reviewed By: antiagainst
Differential Revision: https://reviews.llvm.org/D82198
This patch add support for 'spv.CopyMemory'. The following changes are
introduced:
- 'CopyMemory' op is added to SPIRVOps.td.
- Custom parse and print methods are introduced.
- A few Roundtripping tests are added.
Differential Revision: https://reviews.llvm.org/D82384
Initially, unranked memref descriptors in the LLVM dialect were designed only
to be passed into functions. An assertion was guarding against returning
unranked memrefs from functions in the standard-to-LLVM conversion. This is
insufficient for functions that wish to return an unranked memref such that the
caller does not know the rank in advance, and hence cannot allocate the
descriptor and pass it in as an argument.
Introduce a calling convention for returning unranked memref descriptors as
follows. An unranked memref descriptor always points to a ranked memref
descriptor stored on stack of the current function. When an unranked memref
descriptor is returned from a function, the ranked memref descriptor it points
to is copied to dynamically allocated memory, the ownership of which is
transferred to the caller. The caller is responsible for deallocating the
dynamically allocated memory and for copying the pointed-to ranked memref
descriptor onto its stack.
Provide default lowerings for std.return, std.call and std.indirect_call that
maintain the conversion defined above.
This convention is additionally exercised by a runtime test to guard against
memory errors.
Differential Revision: https://reviews.llvm.org/D82647
Replace any `rank(shape_of(tensor))` that relies on a ranked tensor with the
corresponding constant `const_size`.
Differential Revision: https://reviews.llvm.org/D82077
Summary: The patch optimizes the tiling of parallel loops with static bounds if the number of loop iterations is an integer multiple of the tile size.
Reviewers: herhut, ftynse, bondhugula
Reviewed By: herhut, ftynse
Subscribers: bondhugula, mehdi_amini, rriddle, jpienaar, shauheen, antiagainst, nicolasvasilache, arpith-jacob, mgester, lucyrfox, aartbik, liufengdb, stephenneuendorffer, Joonsoo, grosul1, frgossen, Kayjukh, jurahul, msifontes
Tags: #mlir
Differential Revision: https://reviews.llvm.org/D82003
Use vector compares for the 1-D case. This approach scales much better
than generating insertion operations, and exposes SIMD directly to backend.
Reviewed By: ftynse
Differential Revision: https://reviews.llvm.org/D82402
Introduced `llvm.intr.bitreverse` and `llvm.intr.ctpop` LLVM bit
intrinsics to LLVM dialect. These intrinsics help with SPIR-V to
LLVM conversion, allowing a direct mapping from `spv.BitReverse`
and `spv.BitCount` respectively. Tests are added to `roundtrip.mlir`
and `llvm-intrinsics.mlir`.
Differential Revision: https://reviews.llvm.org/D82285
This patch extends the AccessChainOp index type handling to be able to deal with
all Integer type indices (i.e., all bit-widths and signedness symantics).
There were two ways of achieving this:
1- Backward compatible: The new way of handling the indices will assume that
an index type is i32 by default if not specified in the assembly format,
this way all the old tests would pass correctly.
2- Enforce the format: This unifies the spv.AccessChain Op format and all the old
tests had to be updated to reflect this change or else they fail.
I picked option-2 to unify the Op format and avoid having optional index-type fields
that can lead to somewhat confusing tests format and multiple representations for
the same Op with undocumented assumption that an index is i32 unless stated.
Nonetheless, reverting to option-1 should be straightforward if preferred or needed.
Differential Revision: https://reviews.llvm.org/D81763
Summary:
We already had a parallel loop specialization pass that is used to
enable unrolling and consecutive vectorization by rewriting loops
whose bound is defined as a min of a constant and a dynamic value
into a loop with static bound (the constant) and the minimum as
bound, wrapped into a conditional to dispatch between the two.
This adds the same rewriting for for loops.
Differential Revision: https://reviews.llvm.org/D82189
Allow lhs and rhs to have different type than accumulator/destination. Some
hardware like GPUs support natively operations like uint8xuint8xuint32.
Differential Revision: https://reviews.llvm.org/D82069
Use direct vector constants for the 1-D case. This approach
scales much better than generating elaborate insertion operations
that are eventually folded into a constant. We could of course
generalize the 1-D case to higher ranks, but this simplification
already helps in scaling some microbenchmarks that would formerly
crash on the intermediate IR length.
Reviewed By: reidtatge
Differential Revision: https://reviews.llvm.org/D82144
Summary:
With this change, a function argument attribute of the form
"llvm.align" = <int> will be translated to the corresponding align
attribute in LLVM by the ModuleConversion.
Differential Revision: https://reviews.llvm.org/D82161
muladd can have differenti types for lhs/rhs and acc/destination. Change
verifier and update the test to use supported example.
Differential Revision: https://reviews.llvm.org/D82042
Summary:
Fixed build of D81618
Add a pattern for expanding tanh op into exp form.
A `tanh` is expanded into:
1) 1-exp^{-2x} / 1+exp^{-2x}, if x => 0
2) exp^{2x}-1 / exp^{2x}+1 , if x < 0.
Differential Revision: https://reviews.llvm.org/D82040
Summary:
This is to provide a utility to remove unsupported constraints or for
pipelines that happen to receive these but cannot lower them due to not
supporting assertions.
Differential Revision: https://reviews.llvm.org/D81560
Summary:
- Define the MatrixTimesScalar operation and add roundtrip tests.
- Added a new base class for matrix-specific operations to avoid invalid operands type mismatch check.
- Created a separate Matrix arithmetic operations td file to add more operations in the future.
- Augmented the automatically generated verify method to print more fine-grained error messages.
- Made minor Updates to the matrix type tests.
Reviewers: antiagainst, rriddle, mravishankar
Reviewed By: antiagainst
Subscribers: mehdi_amini, jpienaar, shauheen, nicolasvasilache, arpith-jacob, mgester, lucyrfox, aartbik, liufengdb, stephenneuendorffer, Joonsoo, bader, grosul1, frgossen, Kayjukh, jurahul, msifontes
Tags: #mlir
Differential Revision: https://reviews.llvm.org/D81677
Summary:
Parallel loop tiling did not properly compute the updated loop
indices when tiling, which lead to wrong results.
Differential Revision: https://reviews.llvm.org/D82013
Summary:
This revision replaces MatmulOp, now that DRR rules have been dropped.
This revision also fixes minor parsing bugs and a plugs a few holes to get e2e paths working (e.g. library call emission).
During the replacement the i32 version had to be dropped because only the EDSC operators +, *, etc support type inference.
Deciding on a type-polymorphic behavior, and implementing it, is left for future work.
Reviewers: aartbik
Subscribers: mehdi_amini, rriddle, jpienaar, shauheen, antiagainst, arpith-jacob, mgester, lucyrfox, aartbik, liufengdb, stephenneuendorffer, Joonsoo, grosul1, frgossen, Kayjukh, jurahul, msifontes
Tags: #mlir
Differential Revision: https://reviews.llvm.org/D81935
This revision replaces MatmulOp, now that DRR rules have been dropped.
This revision also fixes minor parsing bugs and a plugs a few holes to get e2e paths working (e.g. library call emission).
During the replacement the i32 version had to be dropped because only the EDSC operators +, *, etc support type inference.
Deciding on a type-polymorphic behavior, and implementing it, is left for future work.
Differential Revision: https://reviews.llvm.org/D79762
This reverts commit 32c757e4f8.
Broke the build bot:
******************** TEST 'MLIR :: Examples/standalone/test.toy' FAILED ********************
[...]
/tmp/ci-KIMiRFcVZt/lib/libMLIRLinalgToLLVM.a(LinalgToLLVM.cpp.o): In function `(anonymous namespace)::ConvertLinalgToLLVMPass::runOnOperation()':
LinalgToLLVM.cpp:(.text._ZN12_GLOBAL__N_123ConvertLinalgToLLVMPass14runOnOperationEv+0x100): undefined reference to `mlir::populateExpandTanhPattern(mlir::OwningRewritePatternList&, mlir::MLIRContext*)'
Summary:
Add a pattern for expanding tanh op into exp form.
A `tanh` is expanded into:
1) 1-exp^{-2x} / 1+exp^{-2x}, if x => 0
2) exp^{2x}-1 / exp^{2x}+1 , if x < 0.
Differential Revision: https://reviews.llvm.org/D81618
Modify structure type in SPIR-V dialect to support:
1) Multiple decorations per structure member
2) Key-value based decorations (e.g., MatrixStride)
This commit kept the Offset decoration separate from members'
decorations container for easier implementation and logical clarity.
As such, all references to Structure layoutinfo are now offsetinfo,
and any member layout defining decoration (e.g., RowMajor for Matrix)
will be add to the members' decorations container along with its
value if any.
Differential Revision: https://reviews.llvm.org/D81426
Add `NoSideEffect` trait to `shape.to_extent_tensor` and
`shape.from_extent_tensor` and defined custom assembly format for the
operations.
Differential Revision: https://reviews.llvm.org/D81158
This option avoids to accidentally reuse variable across -LABEL match,
it can be explicitly opted-in by prefixing the variable name with $
Differential Revision: https://reviews.llvm.org/D81531
Modify structure type in SPIR-V dialect to support:
1) Multiple decorations per structure member
2) Key-value based decorations (e.g., MatrixStride)
This commit kept the Offset decoration separate from members'
decorations container for easier implementation and logical clarity.
As such, all references to Structure layoutinfo are now offsetinfo,
and any member layout defining decoration (e.g., RowMajor for Matrix)
will be add to the members' decorations container along with its
value if any.
Differential Revision: https://reviews.llvm.org/D81426
Summary:
We now support index casting for tensor<index> to tensor<int>. This
better supports compatibility with the Shape dialect.
Differential Revision: https://reviews.llvm.org/D81611
Modify structure type in SPIR-V dialect to support:
1) Multiple decorations per structure member
2) Key-value based decorations (e.g., MatrixStride)
This commit kept the Offset decoration separate from members'
decorations container for easier implementation and logical clarity.
As such, all references to Structure layoutinfo are now offsetinfo,
and any member layout defining decoration (e.g., RowMajor for Matrix)
will be add to the members' decorations container along with its
value if any.
Differential Revision: https://reviews.llvm.org/D81426
Allow for dynamic indices in the `dim` operation.
Rather than an attribute, the index is now an operand of type `index`.
This allows to apply the operation to dynamically ranked tensors.
The correct lowering of dynamic indices remains to be implemented.
Differential Revision: https://reviews.llvm.org/D81551
The operation `get_extent` now accepts the dimension as an operand and is no
longer limited to constant dimensions.
A helper function facilitates the common constant use case.
Differential Revision: https://reviews.llvm.org/D81248
Summary:
Even though this operation is intended for 1d/2d conversions currently,
leaving a semantic hole in the lowering prohibits proper testing of this
operation. This CL adds a straightforward reference implementation for the
missing cases.
Reviewers: nicolasvasilache, mehdi_amini, ftynse, reidtatge
Reviewed By: reidtatge
Subscribers: mehdi_amini, rriddle, jpienaar, shauheen, antiagainst, nicolasvasilache, arpith-jacob, mgester, lucyrfox, liufengdb, stephenneuendorffer, Joonsoo, grosul1, frgossen, Kayjukh, jurahul, msifontes
Tags: #mlir
Differential Revision: https://reviews.llvm.org/D81503
Having the input dumped on failure seems like a better
default: I debugged FileCheck tests for a while without knowing
about this option, which really helps to understand failures.
Remove `-dump-input-on-failure` and the environment variable
FILECHECK_DUMP_INPUT_ON_FAILURE which are now obsolete.
Differential Revision: https://reviews.llvm.org/D81422
The SSA values created with `shape.const_size` are now named depending on the
value.
A constant size of 3, e.g., is now automatically named `%c3`.
Differential Revision: https://reviews.llvm.org/D81249
Summary:
This revision adds a common folding pattern that starts appearing on
vector_transfer ops.
Differential Revision: https://reviews.llvm.org/D81281
This allows verifying op-indepent attributes (e.g., attributes that do not require the op to have been created) before constructing an operation. These include checking whether required attributes are defined or constraints on attributes (such as I32 attribute). This is not perfect (e.g., if one had a disjunctive constraint where one part relied on the op and the other doesn't, then this would not try and extract the op independent from the op dependent).
The next step is to move these out to a trait that could be verified earlier than in the generated method. The first use case is for inferring the return type while constructing the op. At that point you don't have an Operation yet and that ends up in one having to duplicate the same checks, e.g., verify that attribute A is defined before querying A in shape function which requires that duplication. Instead this allows one to invoke a method to verify all the traits and, if this is checked first during verification, then all other traits could use attributes knowing they have been verified.
It is a little bit funny to have these on the adaptor, but I see the adaptor as a place to collect information about the op before the op is constructed (e.g., avoiding stringly typed accessors, verifying what is possible to verify before the op is constructed) while being cheap to use even with constructed op (so layer of indirection between the op constructed/being constructed). And from that point of view it made sense to me.
Differential Revision: https://reviews.llvm.org/D80842
Add support for flat, location, and noperspective decorations in the
serializer and deserializer to be able to process basic shader files
for graphics applications.
Differential Revision: https://reviews.llvm.org/D80837
This revision adds a helper function to hoist vector.transfer_read /
vector.transfer_write pairs out of immediately enclosing scf::ForOp
iteratively, if the following conditions are true:
1. The 2 ops access the same memref with the same indices.
2. All operands are invariant under the enclosing scf::ForOp.
3. No uses of the memref either dominate the transfer_read or are
dominated by the transfer_write (i.e. no aliasing between the write and
the read across the loop)
To improve hoisting opportunities, call the `moveLoopInvariantCode` helper
function on the candidate loop above which to hoist. Hoisting the transfers
results in scf::ForOp yielding the value that originally transited through
memory.
This revision additionally exposes `moveLoopInvariantCode` as a helper in
LoopUtils.h and updates SliceAnalysis to support return scf::For values and
allow hoisting across multiple scf::ForOps.
Differential Revision: https://reviews.llvm.org/D81199
Summary:
This will inline the region to a shape.assuming in the case that the
input witness is found to be statically true.
Differential Revision: https://reviews.llvm.org/D80302
In the case of all inputs being constant and equal, cstr_eq will be
replaced with a true_witness.
Differential Revision: https://reviews.llvm.org/D80303
This allows replacing of this op with a true witness in the case of both
inputs being const_shapes and being found to be broadcastable.
Differential Revision: https://reviews.llvm.org/D80304
This allows assuming_all to be replaced when all inputs are known to be
statically passing witnesses.
Differential Revision: https://reviews.llvm.org/D80306
This will later be used during canonicalization and folding steps to replace
statically known passing constraints.
Differential Revision: https://reviews.llvm.org/D80307
Update linalg to affine lowering for convop to use affine load for input
whenever there is no padding. It had always been using std.loads because
max in index functions (needed for non-zero padding if not materializing
zeros) couldn't be represented in the non-zero padding cases.
In the future, the non-zero padding case could also be made to use
affine - either by materializing or using affine.execute_region. The
latter approach will not impact the scf/std output obtained after
lowering out affine.
Differential Revision: https://reviews.llvm.org/D81191
This simplifies a lot of handling of BoolAttr/IntegerAttr. For example, a lot of places currently have to handle both IntegerAttr and BoolAttr. In other places, a decision is made to pick one which can lead to surprising results for users. For example, DenseElementsAttr currently uses BoolAttr for i1 even if the user initialized it with an Array of i1 IntegerAttrs.
Differential Revision: https://reviews.llvm.org/D81047
This revision adds a helper function to hoist alloc/dealloc pairs and
alloca op out of immediately enclosing scf::ForOp if both conditions are true:
1. all operands are defined outside the loop.
2. all uses are ViewLikeOp or DeallocOp.
This is now considered Linalg-specific and will be generalized on a per-need basis.
Differential Revision: https://reviews.llvm.org/D81152
Add SubgroupId, SubgroupSize and NumSubgroups to GPU dialect ops and add the
lowering of those ops to SPIRV.
Differential Revision: https://reviews.llvm.org/D81042
Summary:
The fusion for tensor_reshape is embedding the information to indexing maps,
thus the exising pattenr also works for indexed_generic ops.
Depends On D80347
Differential Revision: https://reviews.llvm.org/D80348
Summary:
Different from the fusion between generic ops, indices are involved. In this
context, we need to re-map the indices for producer since the fused op is built
on consumer's perspective. This patch supports all combination of the fusion
between indexed_generic ops and generic ops, which includes tests case:
1) generic op as producer and indexed_generic op as consumer.
2) indexed_generic op as producer and generic op as consumer.
3) indexed_generic op as producer and indexed_generic op as consumer.
Differential Revision: https://reviews.llvm.org/D80347
Summary:
Progressive lowering of vector.transpose into an operation that
is closer to an intrinsic, and thus the hardware ISA. Currently
under the common vector transform testing flag, as we prepare
deploying this transformation in the LLVM lowering pipeline.
Reviewers: nicolasvasilache, reidtatge, andydavis1, ftynse
Reviewed By: nicolasvasilache, ftynse
Subscribers: mehdi_amini, rriddle, jpienaar, shauheen, antiagainst, nicolasvasilache, arpith-jacob, mgester, lucyrfox, liufengdb, stephenneuendorffer, Joonsoo, grosul1, frgossen, Kayjukh, jurahul, llvm-commits
Tags: #llvm, #mlir
Differential Revision: https://reviews.llvm.org/D80772
This commit adds basic matrix type support to the SPIR-V dialect
including type definition, IR assembly, parsing, printing, and
(de)serialization.
Differential Revision: https://reviews.llvm.org/D80594
This revision replaces the load + vector.type_cast by appropriate vector transfer
operations. These play more nicely with other vector abstractions and canonicalization
patterns and lower to load/store with or without masks when appropriate.
Differential Revision: https://reviews.llvm.org/D80809
Summary:
Implemented the basic changes for defining master operation in OpenMP.
It uses the generic parser and printer.
Reviewed By: kiranchandramohan, ftynse
Differential Revision: https://reviews.llvm.org/D80689
This revision adds custom rewrites for patterns that arise during linalg structured
ops vectorization. These patterns allow the composition of linalg promotion,
vectorization and removal of redundant copies.
The patterns are voluntarily limited and restrictive atm.
More robust behavior will be implemented once more powerful side effect modeling and analyses are available on view/subview.
On the transfer_read side, the following pattern is rewritten:
```
%alloc = ...
[optional] %view = std.view %alloc ...
%subView = subview %allocOrView ...
[optional] linalg.fill(%allocOrView, %cst) ...
...
linalg.copy(%in, %subView) ...
vector.transfer_read %allocOrView[...], %cst ...
```
into
```
[unchanged] %alloc = ...
[unchanged] [optional] %view = std.view %alloc ...
[unchanged] [unchanged] %subView = subview %allocOrView ...
...
vector.transfer_read %in[...], %cst ...
```
On the transfer_write side, the following pattern is rewriten:
```
%alloc = ...
[optional] %view = std.view %alloc ...
%subView = subview %allocOrView...
...
vector.transfer_write %..., %allocOrView[...]
linalg.copy(%subView, %out)
```
Differential Revision: https://reviews.llvm.org/D80728
operands of Generic ops.
Unit-extent dimensions are typically used for achieving broadcasting
behavior. The pattern added (along with canonicalization patterns
added previously) removes the use of unit-extent dimensions, and
instead uses a more canonical representation of the computation. This
new pattern is not added as a canonicalization for now since it
entails adding additional reshape operations. A pass is added to
exercise these patterns, along with an API entry to populate a
patterns list with these patterns.
Differential Revision: https://reviews.llvm.org/D79766
The operation `num_elements` determines the number of elements for a given
shape.
That is the product of its dimensions.
Differential Revision: https://reviews.llvm.org/D80281
Add the two conversion operations `index_to_size` and `size_to_index` to the
shape dialect.
This facilitates the conversion of index types between the shape and the
standard dialect.
Differential Revision: https://reviews.llvm.org/D80280
Summary:
Index is the proper type for storing shapes when constant folding, so
this fixes the previous code (which was using i64).
Differential Revision: https://reviews.llvm.org/D80600
Summary:
This includes a basic implementation for the OpenMP parallel
operation without a custom pretty-printer and parser.
The if, num_threads, private, shared, first_private, last_private,
proc_bind and default clauses are included in this implementation.
Currently the reduction clause is omitted as it is more complex and
requires analysis to see if we can share implementation with the loop
dialect. The allocate clause is also omitted.
A discussion about the design of this operation can be found here:
https://llvm.discourse.group/t/openmp-parallel-operation-design-issues/686
The current OpenMP Specification can be found here:
https://www.openmp.org/wp-content/uploads/OpenMP-API-Specification-5.0.pdf
Co-authored-by: Kiran Chandramohan <kiran.chandramohan@arm.com>
Reviewers: jdoerfert
Subscribers: mgorny, yaxunl, kristof.beyls, guansong, mehdi_amini, rriddle, jpienaar, shauheen, antiagainst, nicolasvasilache, arpith-jacob, mgester, lucyrfox, aartbik, liufengdb, Joonsoo, grosul1, frgossen, Kayjukh, llvm-commits
Tags: #llvm
Differential Revision: https://reviews.llvm.org/D79410
alloc/dealloc/copies.
Add options to LinalgPromotion to use callbacks for implementating the
allocation, deallocation of buffers used for the promoted subviews,
and to copy data into and from the original subviews to the allocated
buffers.
Also some misc. cleanup of the code.
Differential Revision: https://reviews.llvm.org/D80365
Modifying the loop nest builder for generating scf.parallel loops to
not generate scf.parallel loops for non-parallel iterator types in
Linalg operations. The existing implementation incorrectly generated
scf.parallel for all tiled loops. It is rectified by refactoring logic
used while lowering to loops that accounted for this.
Differential Revision: https://reviews.llvm.org/D80188
Summary:
This op extracts an extent from a shape.
This also is the first op which constant folds to shape.const_size,
which revealed that shape.const_size needs a folder (ConstantLike ops
seem to always need folders for the constant folding infra to work).
Differential Revision: https://reviews.llvm.org/D80394
This revision expands the types of vector contractions that can be lowered to vector.outerproduct.
All 8 permutation cases are support.
The idiomatic manipulation of AffineMap written declaratively makes this straightforward.
In the process a bug with the vector.contract verifier was uncovered.
The vector shape verification part of the contract op is rewritten to use AffineMap composition.
One bug in the vector `ops.mlir` test is fixed and a new case not yet captured is added
to the vector`invalid.mlir` test.
Differential Revision: https://reviews.llvm.org/D80393
This revision adds the additional lowering and exposes the patterns at a finer granularity for better programmatic reuse. The unit test makes use of the finer grained pattern for simpler checks.
As the ContractionOpLowering is exposed programmatically, cleanup opportunities appear and static class methods are turned into free functions with static visibility.
Differential Revision: https://reviews.llvm.org/D80375
Enable inset/extract/construct composite ops as well as access chain for
cooperative matrix. ConstantComposite requires more change and will be done in
a separate patch. Also fix the getNumElements function for coopMatrix per
feedback from Jeff Bolz. The number of element is implementation dependent so
it cannot be known at compile time.
Differential Revision: https://reviews.llvm.org/D80321
Adds support for cooperative matrix support for arithmetic and cast
instructions. It also adds cooperative matrix store, muladd and matrixlength
instructions which are part of the extension.
Differential Revision: https://reviews.llvm.org/D80181
Summary:
This revision refactors the Linalg tiling pass to be written as pattern applications and retires the use of the folder in Linalg tiling.
In the early days, tiling was written as a pass that would create (partially) folded and canonicalized operations on the fly for better composability.
As this evolves towards composition of patterns, the pass-specific folder is counter-productive and is retired.
The tiling options struct evolves to take a tile size creation function which allows materializing tile sizes on the fly (in particular constant tile sizes). This plays better with folding and DCE.
With the folder going away in Tiling, the check on whether subviews are the same in linalg fusion needs to be more robust. This revision also implements such a check.
In the current form, there are still some canonicalizations missing due to AffineMin/Max ops fed by scf::ForOp. These will be improved at a later time.
Differential Revision: https://reviews.llvm.org/D80267
Summary:
Additionally, this adds traits and builder methods to AssumingYieldOp
and names the input witness to the AssumingOp.
Differential Revision: https://reviews.llvm.org/D80187
Add a new type to SPIRV dialect for cooperative matrix and add new op for
cooperative matrix load. This is missing most instructions to support
cooperative matrix extension but this is a stop-gap patch to avoid creating big
review.
Differential Revision: https://reviews.llvm.org/D80043
Summary:
This is a basic op needed for creating shapes from SSA values
representing the extents.
Differential Revision: https://reviews.llvm.org/D79833
Implemented tangent op from SPIR-V's GLSL extended instruction set.
Added a round-trip and serialization/deserialization tests for the op.
Differential Revision: https://reviews.llvm.org/D80152
Summary:
This patch adds support for flush operation in OpenMP dialect and translation of this construct to LLVM IR.
The OpenMP IRBuilder is used for this translation.
The patch includes code changes and testcase modifications.
Reviewed By: ftynse, kiranchandramohan
Differential Revision: https://reviews.llvm.org/D79937
For now the promoted buffer is indexed using the `full view`. The full view might be
slightly bigger than the partial view (which is accounting for boundaries).
Unfortunately this does not compose easily with other transformations when multiple buffers
with shapes related to each other are involved.
Take `linalg.matmul A B C` (with A of size MxK, B of size KxN and C of size MxN) and suppose we are:
- Tiling over M by 100
- Promoting A only
This is producing a `linalg.matmul promoted_A B subview_C` where `promoted_A` is a promoted buffer
of `A` of size (100xK) and `subview_C` is a subview of size mxK where m could be smaller than 100 due
to boundaries thus leading to a possible incorrect behavior.
We propose to:
- Add a new parameter to the tiling promotion allowing to enable the use of the full tile buffer.
- By default all promoted buffers will be indexed by the partial view.
Note that this could be considered as a breaking change in comparison to the way the tiling promotion
was working.
Differential Revision: https://reviews.llvm.org/D79927
Summary:
Vector transfer ops semantic is extended to allow specifying a per-dimension `masked`
attribute. When the attribute is false on a particular dimension, lowering to LLVM emits
unmasked load and store operations.
Differential Revision: https://reviews.llvm.org/D80098
Summary:
This revision makes the use of vector transfer operatons more idiomatic by
allowing to omit and inferring the permutation_map.
Differential Revision: https://reviews.llvm.org/D80092
Summary:
First, compact implementation of lowering to LLVM IR. A bit more
challenging than the constant mask due to the dynamic indices, of course.
I like to hear if there are more efficient ways of doing this in LLVM,
but this for now at least gives us a functional reference implementation.
Reviewers: nicolasvasilache, ftynse, bkramer, reidtatge, andydavis1, mehdi_amini
Reviewed By: nicolasvasilache
Subscribers: mehdi_amini, rriddle, jpienaar, shauheen, antiagainst, nicolasvasilache, arpith-jacob, mgester, lucyrfox, liufengdb, stephenneuendorffer, Joonsoo, grosul1, frgossen, Kayjukh, jurahul, llvm-commits
Tags: #llvm
Differential Revision: https://reviews.llvm.org/D79954
This revision starts decoupling the include the kitchen sink behavior of Linalg to LLVM lowering by inserting a -convert-linalg-to-std pass.
The lowering of linalg ops to function calls was previously lowering to memref descriptors by having both linalg -> std and std -> LLVM patterns in the same rewrite.
When separating this step, a new issue occurred: the layout is automatically type-erased by this process. This revision therefore introduces memref casts to perform these type erasures explicitly. To connect everything end-to-end, the LLVM lowering of MemRefCastOp is relaxed because it is artificially more restricted than the op semantics. The op semantics already guarantee that source and target MemRefTypes are cast-compatible. An invalid lowering test now becomes valid and is removed.
Differential Revision: https://reviews.llvm.org/D79468
This patch adds `affine.vector_load` and `affine.vector_store` ops to
the Affine dialect and lowers them to `vector.transfer_read` and
`vector.transfer_write`, respectively, in the Vector dialect.
Reviewed By: bondhugula, nicolasvasilache
Differential Revision: https://reviews.llvm.org/D79658
All ops of the SCF dialect now use the `scf.` prefix instead of `loop.`. This
is a part of dialect renaming.
Differential Revision: https://reviews.llvm.org/D79844
The existing implementation of SubViewOp::getRanges relies on all
offsets/sizes/strides to be dynamic values and does not work in
combination with canonicalization. This revision adds a
SubViewOp::getOrCreateRanges to create the missing constants in the
canonicalized case.
This allows reactivating the fused pass with staged pattern
applications.
However another issue surfaces that the SubViewOp verifier is now too
strict to allow folding. The existing folding pattern is turned into a
canonicalization pattern which rewrites memref_cast + subview into
subview + memref_cast.
The transform-patterns-matmul-to-vector can then be reactivated.
Differential Revision: https://reviews.llvm.org/D79759
This is only valid if the source tensors (result tensor) is static
shaped with all unit-extents when the reshape is collapsing
(expanding) dimensions.
Differential Revision: https://reviews.llvm.org/D79764
Summary:
Makes this operation runnable on CPU by generating MLIR instructions
that are eventually folded into an LLVM IR constant for the mask.
Reviewers: nicolasvasilache, ftynse, reidtatge, bkramer, andydavis1
Reviewed By: nicolasvasilache, ftynse, andydavis1
Subscribers: mehdi_amini, rriddle, jpienaar, shauheen, antiagainst, nicolasvasilache, arpith-jacob, mgester, lucyrfox, liufengdb, stephenneuendorffer, Joonsoo, grosul1, frgossen, Kayjukh, llvm-commits
Tags: #llvm
Differential Revision: https://reviews.llvm.org/D79815
The main objective of this revision is to change the way static information is represented, propagated and canonicalized in the SubViewOp.
In the current implementation the issue is that canonicalization may strictly lose information because static offsets are combined in irrecoverable ways into the result type, in order to fit the strided memref representation.
The core semantics of the op do not change but the parser and printer do: the op always requires `rank` offsets, sizes and strides. These quantities can now be either SSA values or static integer attributes.
The result type is automatically deduced from the static information and more powerful canonicalizations (as powerful as the representation with sentinel `?` values allows). Previously static information was inferred on a best-effort basis from looking at the source and destination type.
Relevant tests are rewritten to use the idiomatic `offset: x, strides : [...]`-form. Bugs are corrected along the way that were not trivially visible in flattened strided memref form.
Lowering to LLVM is updated, simplified and now supports all cases.
A mixed static-dynamic mode test that wouldn't previously lower is added.
It is an open question, and a longer discussion, whether a better result type representation would be a nicer alternative. For now, the subview op carries the required semantic.
Differential Revision: https://reviews.llvm.org/D79662
This reverts commit 80d133b24f.
Per Stephan Herhut: The canonicalizer pattern that was added creates
forms of the subview op that cannot be lowered.
This is shown by failing Tensorflow XLA tests such as:
tensorflow/compiler/xla/service/mlir_gpu/tests:abs.hlo.test
Will provide more details offline, they rely on logs from private CI.
Summary:
The main objective of this revision is to change the way static information is represented, propagated and canonicalized in the SubViewOp.
In the current implementation the issue is that canonicalization may strictly lose information because static offsets are combined in irrecoverable ways into the result type, in order to fit the strided memref representation.
The core semantics of the op do not change but the parser and printer do: the op always requires `rank` offsets, sizes and strides. These quantities can now be either SSA values or static integer attributes.
The result type is automatically deduced from the static information and more powerful canonicalizations (as powerful as the representation with sentinel `?` values allows). Previously static information was inferred on a best-effort basis from looking at the source and destination type.
Relevant tests are rewritten to use the idiomatic `offset: x, strides : [...]`-form. Bugs are corrected along the way that were not trivially visible in flattened strided memref form.
It is an open question, and a longer discussion, whether a better result type representation would be a nicer alternative. For now, the subview op carries the required semantic.
Reviewers: ftynse, mravishankar, antiagainst, rriddle!, andydavis1, timshen, asaadaldien, stellaraccident
Reviewed By: mravishankar
Subscribers: aartbik, bondhugula, mehdi_amini, rriddle, jpienaar, shauheen, antiagainst, arpith-jacob, mgester, lucyrfox, liufengdb, stephenneuendorffer, Joonsoo, bader, grosul1, frgossen, Kayjukh, llvm-commits
Tags: #llvm
Differential Revision: https://reviews.llvm.org/D79662
Summary:
This revision introduces a helper function to allow applying rewrite patterns, interleaved with more global transformations, in a staged fashion:
1. the first stage consists of an OwningRewritePatternList. The RewritePattern in this list are applied once and in order.
2. the second stage consists of a single OwningRewritePattern that is applied greedily until convergence.
3. the third stage consists of applying a lambda, generally used for non-local transformation effects.
This allows creating custom fused transformations where patterns can be ordered and applied at a finer granularity than a sequence of traditional compiler passes.
A test that exercises these behaviors is added.
Differential Revision: https://reviews.llvm.org/D79518
This [discussion](https://llvm.discourse.group/t/viewop-isnt-expressive-enough/991/2) raised some concerns with ViewOp.
In particular, the handling of offsets is incorrect and does not match the op description.
Note that with an elemental type change, offsets cannot be part of the type in general because sizeof(srcType) != sizeof(dstType).
Howerver, offset is a poorly chosen term for this purpose and is renamed to byte_shift.
Additionally, for all intended purposes, trying to support non-identity layouts for this op does not bring expressive power but rather increases code complexity.
This revision simplifies the existing semantics and implementation.
This simplification effort is voluntarily restrictive and acts as a stepping stone towards supporting richer semantics: treat the non-common cases as YAGNI for now and reevaluate based on concrete use cases once a round of simplification occurred.
Differential revision: https://reviews.llvm.org/D79541
This dialect contains various structured control flow operaitons, not only
loops, reflect this in the name. Drop the Ops suffix for consistency with other
dialects.
Note that this only moves the files and changes the C++ namespace from 'loop'
to 'scf'. The visible IR prefix remains the same and will be updated
separately. The conversions will also be updated separately.
Differential Revision: https://reviews.llvm.org/D79578
Originally, these operations were folded only if all expressions in their
affine maps could be folded to a constant expression that can be then subject
to numeric min/max computation. This introduces a more advanced version that
partially folds the affine map by lifting individual constant expression in it
even if some of the expressions remain variable. The folding can update the
operation in place to use a simpler map. Note that this is not as powerful as
canonicalization, in particular this does not remove dimensions or symbols that
became useless. This allows for better composition of Linalg tiling and
promotion transformation, where the latter can handle some canonical forms of
affine.min that the folding can now produce.
Differential Revision: https://reviews.llvm.org/D79502
Summary:
Adds the loop unroll transformation for loop::ForOp.
Adds support for promoting the body of single-iteration loop::ForOps into its containing block.
Adds check tests for loop::ForOps with dynamic and static lower/upper bounds and step.
Care was taken to share code (where possible) with the AffineForOp unroll transformation to ease maintenance and potential future transition to a LoopLike construct on which loop transformations for different loop types can implemented.
Reviewers: ftynse, nicolasvasilache
Reviewed By: ftynse
Subscribers: bondhugula, mgorny, zzheng, mehdi_amini, rriddle, jpienaar, shauheen, antiagainst, nicolasvasilache, arpith-jacob, mgester, lucyrfox, aartbik, liufengdb, Joonsoo, grosul1, frgossen, Kayjukh, llvm-commits
Tags: #llvm
Differential Revision: https://reviews.llvm.org/D79184
Adding this pattern reduces code duplication. There is no need to have a
custom implementation for lowering to llvm.cmpxchg.
Differential Revision: https://reviews.llvm.org/D78753
This revision adds support for merging identical blocks, or those with the same operations that branch to the same successors. Operands that mismatch between the different blocks are replaced with new block arguments added to the merged block.
Differential Revision: https://reviews.llvm.org/D79134
Linalg transformations are currently exposed as DRRs.
Unfortunately RewriterGen does not play well with the line of work on named linalg ops which require variadic operands and results.
Additionally, DRR is arguably not the right abstraction to expose compositions of such patterns that don't rely on SSA use-def semantics.
This revision abandons DRRs and exposes manually written C++ patterns.
Refactorings and cleanups are performed to uniformize APIs.
This refactoring will allow replacing the currently manually specified Linalg named ops.
A collateral victim of this refactoring is the `tileAndFuse` DRR, and the one associated test, which will be revived at a later time.
Lastly, the following 2 tests do not add value and are altered:
- a dot_perm tile + interchange test does not test anything new and is removed
- a dot tile + lower to loops does not need 2-D tiling and is trimmed.
This is useful for several reasons:
* In some situations the user can guarantee that thread-safety isn't necessary and don't want to pay the cost of synchronization, e.g., when parsing a very large module.
* For things like logging threading is not desirable as the output is not guaranteed to be in stable order.
This flag also subsumes the pass manager flag for multi-threading.
Differential Revision: https://reviews.llvm.org/D79266
Summary:
This is an initial version, currently supports OpString and OpLine
for autogenerated operations during (de)serialization.
Differential Revision: https://reviews.llvm.org/D79091
Summary:
This revision cleans up a layer of complexity in ScopedContext and uses InsertGuard instead of previously manual bookkeeping.
The method `getBuilder` is renamed to `getBuilderRef` and spurious copies of OpBuilder are tracked.
This results in some canonicalizations not happening anymore in the Linalg matmul to vector test. This test is retired because relying on DRRs for this has been shaky at best. The solution will be better support to write fused passes in C++ with more idiomatic pattern composition and application.
Differential Revision: https://reviews.llvm.org/D79208
This revision adds support to allow named ops to lower to loops.
Linalg.batch_matmul successfully lowers to loops and to LLVM.
In the process, this test also activates linalg to affine loops.
However padded convolutions to not lower to affine.load atm so this revision overrides the type of underlying load / store operation.
Differential Revision: https://reviews.llvm.org/D79135
Lei Zhang