The current modeling of LLVM IR types in MLIR is based on the LLVMType class
that wraps a raw `llvm::Type *` and delegates uniquing, printing and parsing to
LLVM itself. This is model makes thread-safe type manipulation hard and is
being progressively replaced with a cleaner MLIR model that replicates the type
system. In the new model, LLVMType will no longer have an underlying LLVM IR
type. Restrict access to this type in the current model in preparation for the
change.
Reviewed By: nicolasvasilache
Differential Revision: https://reviews.llvm.org/D84389
Operating on indices and extent tensors directly, the type conversion is no
longer needed for the supported cases.
Differential Revision: https://reviews.llvm.org/D84442
This adds conversions for const_size and to_extent_tensor. Also, cast-like operations are now folded away if the source and target types are the same.
Differential Revision: https://reviews.llvm.org/D84745
Conversion of `spv.BranchConditional` now supports branch weights
that are mapped to weights vector in `llvm.cond_br`.
Reviewed By: antiagainst
Differential Revision: https://reviews.llvm.org/D84657
Added a check for 'Function' storage class in `spv.globalVariable`
verifier since it only can be used with `spv.Variable`.
Reviewed By: antiagainst
Differential Revision: https://reviews.llvm.org/D84731
This patch adds support of Volatile and Nontemporal
memory accesses to `spv.Load` and `spv.Store`. These attributes are
modelled with a `volatile` and `nontemporal` flags.
Reviewed By: antiagainst
Differential Revision: https://reviews.llvm.org/D84739
- Add getArgumentTypes() to Region (missed from before)
- Adopt Region argument API in `hasMultiplyAddBody`
- Fix 2 typos in comments
Differential Revision: https://reviews.llvm.org/D84807
The MemRefDataFlow pass does store to load forwarding
only for affine store/loads. This patch updates the pass
to use affine read/write interface which enables vector
forwarding.
Reviewed By: dcaballe, bondhugula, ftynse
Differential Revision: https://reviews.llvm.org/D84302
For the purpose of vector transforms, the Tablegen-based infra is subsumed by simple C++ pattern application. Deprecate declarative transforms whose complexity does not pay for itself.
Differential Revision: https://reviews.llvm.org/D84753
Do not return error code, instead return created resource handles or void. Error reporting is done by the library function.
Reviewed By: herhut
Differential Revision: https://reviews.llvm.org/D84660
The current transformation to shape.reduce does not support tensor values.
This adds the required changes to make that work, including fixing the builder
for shape.reduce.
Differential Revision: https://reviews.llvm.org/D84744
- replace DotOp, now that DRR rules have been dropped.
- Capture arguments mismatch in the parser. The number of parsed arguments must
equal the number of expected arguments.
Reviewed By: ftynse, nicolasvasilache
Differential Revision: https://reviews.llvm.org/D82952
The LowerAffine psas was a FunctionPass only for legacy
reasons. Making this Op-agnostic allows it to be used from command
line when affine expressions are within operations other than
`std.func`.
Differential Revision: https://reviews.llvm.org/D84590
linalg.indexed_generic (consumer) with tensor arguments.
The implementation of fusing std.constant producer with a
linalg.indexed_generic consumer was already in place. It is exposed
with this change. Also cleaning up some of the patterns that implement
the fusion to not be templated, thereby avoiding lot of conditional
checks for calling the right instantiation.
Differential Revision: https://reviews.llvm.org/D84566
Introduce support for mutable storage in the StorageUniquer infrastructure.
This makes MLIR have key-value storage instead of just uniqued key storage. A
storage instance now contains a unique immutable key and a mutable value, both
stored in the arena allocator that belongs to the context. This is a
preconditio for supporting recursive types that require delayed initialization,
in particular LLVM structure types. The functionality is exercised in the test
pass with trivial self-recursive type. So far, recursive types can only be
printed in parsed in a closed type system. Removing this restriction is left
for future work.
Differential Revision: https://reviews.llvm.org/D84171
This patch introduces 2 new optional attributes to `llvm.load`
and `llvm.store` ops: `volatile` and `nontemporal`. These attributes
are translated into proper LLVM as a `volatile` marker and a metadata node
respectively. They are also helpful with SPIR-V to LLVM dialect conversion
since they are the mappings for `Volatile` and `NonTemporal` Memory Operands.
Reviewed By: ftynse
Differential Revision: https://reviews.llvm.org/D84396
This diff provides a concrete test case for the error that will be raised when the iteration space is non hyper-rectangular.
The corresponding emission method for this error message has been changed as well.
Differential Revision: https://reviews.llvm.org/D84531
Previous changes generalized some of the operands and results. Complete
a larger group of those to simplify progressive lowering. Also update
some of the declarative asm form due to generalization. Tried to keep it
mostly mechanical.
Based on https://reviews.llvm.org/D84439 but less restrictive, else we
don't allow shape_of to be able to produce a ranked output and doesn't
allow for iterative refinement here. We can consider making it more
restrictive later.
This patch introduces conversion pattern for `spv.Store` and `spv.Load`.
Only op with `Function` Storage Class is supported at the moment
because `spv.GlobalVariable` has not been introduced yet. If the op
has memory access attribute, then there are the following cases.
If the access is `Aligned`, add alignment to the op builder. Otherwise
the conversion fails as other cases are not supported yet because they
require additional attributes for `llvm.store`/`llvm.load` ops: e.g.
`volatile` and `nontemporal`.
Reviewed By: antiagainst
Differential Revision: https://reviews.llvm.org/D84236
The patch introduces the conversion pattern for function-level
`spv.Variable`. It is modelled as `llvm.alloca` op. If initialized, then
additional store instruction is used. Note that there is no initialization
for arrays and structs since constants of these types are not supported in
LLVM dialect yet. Also, at the moment initialisation is only possible via
`spv.constant` (since `spv.GlobalVariable` conversion is not implemented
yet).
The input code has some scoping is not taken into account and will be
addressed in a different patch.
Reviewed By: ftynse
Differential Revision: https://reviews.llvm.org/D84224
This concerns `from/to_extent_tensor`, `size_to_index`, `index_to_size`, and
`const_size` conversion patterns. The new lowering will work directly on indices
and extent tensors. The shape and size values will allow for error values but
are not yet supported by the dialect conversion.
Differential Revision: https://reviews.llvm.org/D84436
The operation `shape.shape_of` now returns an extent tensor `tensor<?xindex>` in
cases when no error are possible. All consuming operation will eventually accept
both, shapes and extent tensors.
Differential Revision: https://reviews.llvm.org/D84160
The default lowering of `assert` calls `abort` in case the assertion is
violated. The failure message is ignored but should be used by custom lowerings
that can assume more about their environment.
Differential Revision: https://reviews.llvm.org/D83886
The operation `shape.const_shape` was used for constants of type shape only.
We can now also use it to create constant extent tensors.
Differential Revision: https://reviews.llvm.org/D84157
This patch introduces branch weights metadata to `llvm.cond_br` op in
LLVM Dialect. It is modelled as optional `ElementsAttr`, for example:
```
llvm.cond_br %cond weights(dense<[1, 3]> : vector<2xi32>), ^bb1, ^bb2
```
When exporting to proper LLVM, this attribute is transformed into metadata
node. The test for metadata creation is added to `../Target/llvmir.mlir`.
Reviewed By: ftynse
Differential Revision: https://reviews.llvm.org/D83658
This revision adds support for much deeper type conversion integration into the conversion process, and enables auto-generating cast operations when necessary. Type conversions are now largely automatically managed by the conversion infra when using a ConversionPattern with a provided TypeConverter. This removes the need for patterns to do type cast wrapping themselves and moves the burden to the infra. This makes it much easier to perform partial lowerings when type conversions are involved, as any lingering type conversions will be automatically resolved/legalized by the conversion infra.
To support this new integration, a few changes have been made to the type materialization API on TypeConverter. Materialization has been split into three separate categories:
* Argument Materialization: This type of materialization is used when converting the type of block arguments when calling `convertRegionTypes`. This is useful for contextually inserting additional conversion operations when converting a block argument type, such as when converting the types of a function signature.
* Source Materialization: This type of materialization is used to convert a legal type of the converter into a non-legal type, generally a source type. This may be called when uses of a non-legal type persist after the conversion process has finished.
* Target Materialization: This type of materialization is used to convert a non-legal, or source, type into a legal, or target, type. This type of materialization is used when applying a pattern on an operation, but the types of the operands have not yet been converted.
Differential Revision: https://reviews.llvm.org/D82831
The `makeTiledViews` did not use the sizes of the tiled views based on
the result of the loop bound inference computation. This manifested as
an error in computing tile sizes with convolution where not all the
result expression of concatenated affine maps are simple
AffineDimExpr.
Differential Revision: https://reviews.llvm.org/D84366
Right now there is a branching for 2 functions based on whether target map has
symbols or not. In this commit these functions are merged into one.
Furthermore, emitting does not require inverse and map applying as it computes
the correct Range in a single step and thus reduces unnecessary overhead.
Differential Revision: https://reviews.llvm.org/D83756
linalg.conv does not support memrefs with rank smaller than 3 as stated here:
https://www.tensorflow.org/versions/r2.0/api_docs/python/tf/nn/convolution
However it does not verify it and thus crashes with "LLVM ERROR: out of memory"
error for 1D case and "nWin > 0 && "expected at least one window dimension"" assertion
for 2D case. This commit adds check for that in the verification method.
Differential Revision: https://reviews.llvm.org/D84317
Loop bound inference is right now very limited as it supports only permutation maps and thus
it is impossible to implement convolution with linalg.generic as it requires more advanced
loop bound inference. This commits solves it for the convolution case.
Depends On D83158
Differential Revision: https://reviews.llvm.org/D83191
This patch refactors a small part of the Super Vectorizer code to
a utility so that it can be used independently from the pass. This
aligns vectorization with other utilities that we already have for loop
transformations, such as fusion, interchange, tiling, etc.
Reviewed By: nicolasvasilache
Differential Revision: https://reviews.llvm.org/D84289
The underlying infrastructure supports this already, just add the
pattern matching for linalg.generic.
Differential Revision: https://reviews.llvm.org/D84335
AllocOp is updated in normalizeMemref(AllocOp allocOp), but, when the
AllocOp has `alignment` attribute, it was ignored and updated AllocOp
does not have `alignment` attribute. This patch fixes it.
Differential Revision: https://reviews.llvm.org/D83656
Introduces the scatter/gather operations to the Vector dialect
(important memory operations for sparse computations), together
with a first reference implementation that lowers to the LLVM IR
dialect to enable running on CPU (and other targets that support
the corresponding LLVM IR intrinsics).
The operations can be used directly where applicable, or can be used
during progressively lowering to bring other memory operations closer to
hardware ISA support for a gather/scatter. The semantics of the operation
closely correspond to those of the corresponding llvm intrinsics.
Note that the operation allows for a dynamic index vector (which is
important for sparse computations). However, this first reference
lowering implementation "serializes" the address computation when
base + index_vector is converted to a vector of pointers. Exploring
how to use SIMD properly during these step is TBD. More general
memrefs and idiomatic versions of striding are also TBD.
Reviewed By: arpith-jacob
Differential Revision: https://reviews.llvm.org/D84039
This patch introduces conversion pattern for `spv.selection` op.
The conversion can only be applied to selection with all blocks being
reachable. Moreover, selection with control attributes "Flatten" and
"DontFlatten" is not supported.
Since the `PatternRewriter` hook for block merging has not been implemented
for `ConversionPatternRewriter`, merge and continue blocks are kept
separately.
Reviewed By: antiagainst, ftynse
Differential Revision: https://reviews.llvm.org/D83860
Alex Zinenko