Added a notification in the placeholder section. While writing things
like preciate of an attribute, we may embed certain placeholder in the C
expression. Note that the type of the placeholder is only guaranteed to
be the base type like mlir::Type, it's better not to use the derived
type which is based on the implementation.
Reviewed By: mehdi_amini
Differential Revision: https://reviews.llvm.org/D112396
Using callbacks for allocation/deallocation allows users to override
the default.
Also add an option to comprehensive bufferization pass to use `alloca`
instead of `alloc`s. Note that this option is just for testing. The
option to use `alloca` does not work well with the option to allow for
returning memrefs.
Using callbacks for allocation/deallocation allows users to override
the default.
Also add an option to comprehensive bufferization pass to use `alloca`
instead of `alloc`s. Note that this option is just for testing. The
option to use `alloca` does not work well with the option to allow for
returning memrefs.
Differential Revision: https://reviews.llvm.org/D112166
In several cases, operation result types can be unambiguously inferred from
operands and attributes at operation construction time. Stop requiring the user
to provide these types as arguments in the ODS-generated constructors in Python
bindings. In particular, handle the SameOperandAndResultTypes and
FirstAttrDerivedResultType traits as well as InferTypeOpInterface using the
recently added interface support. This is a significant usability improvement
for IR construction, similar to what C++ ODS provides.
Depends On D111656
Reviewed By: gysit
Differential Revision: https://reviews.llvm.org/D111811
Introduce the initial support for operation interfaces in C API and Python
bindings. Interfaces are a key component of MLIR's extensibility and should be
available in bindings to make use of full potential of MLIR.
This initial implementation exposes InferTypeOpInterface all the way to the
Python bindings since it can be later used to simplify the operation
construction methods by inferring their return types instead of requiring the
user to do so. The general infrastructure for binding interfaces is defined and
InferTypeOpInterface can be used as an example for binding other interfaces.
Reviewed By: gysit
Differential Revision: https://reviews.llvm.org/D111656
This removes duplication and makes nesting more clear.
It also reduces the amount of changes necessary for exposing future options.
Differential revision: https://reviews.llvm.org/D112344
This allows to clear an OpPassManager and populated it again with a new
pipeline, while preserving all the other options (including instrumentations).
Differential Revision: https://reviews.llvm.org/D112393
This patch fixes a bug in implementation `mergeSymbolIds` where symbol
identifiers were not unique after merging them. Asserts for checking uniqueness
before and after the merge are also added. The asserts checking uniqueness
after the merge fail without the fix on existing test cases.
Reviewed By: arjunp
Differential Revision: https://reviews.llvm.org/D111958
This removes duplication and makes nesting more clear.
It also reduces the amount of changes necessary for exposing future options.
Differential revision: https://reviews.llvm.org/D112344
This patch adds a polynomial approximation that matches the
approximation in Eigen.
Note that the approximation only applies to vectorized inputs;
the scalar rsqrt is left unmodified.
The approximation is protected with a flag since it emits an AVX2
intrinsic (generated via the X86Vector). This is the only reasonably
clean way that I could find to generate the exact approximation that
I wanted (i.e. an identical one to Eigen's).
I considered two alternatives:
1. Introduce a Rsqrt intrinsic in LLVM, which doesn't exist yet.
I believe this is because there is no definition of Rsqrt that
all backends could agree on, since hardware instructions that
implement it have widely varying degrees of precision.
This is something that the standard could mandate, but Rsqrt is
not part of IEEE754, so I don't think this option is feasible.
2. Emit fdiv(1.0, sqrt) with fast math flags to allow reciprocal
transformations. Although portable, this doesn't allow us
to generate exactly the code we want; it is the LLVM backend,
and not MLIR, who controls what code is generated based on the
target CPU.
Reviewed By: ezhulenev
Differential Revision: https://reviews.llvm.org/D112192
Pass the modifiers from the Flang parser to FIR/MLIR workshare
loop operation.
Not yet supporting the SIMD modifier, which is a bit more work
than just adding it to the list of modifiers, so will go in a
separate patch.
This adds a new field to the WsLoopOp.
Also add test for dynamic WSLoop, checking that dynamic schedule calls
the init and next functions as expected.
Reviewed By: ftynse
Differential Revision: https://reviews.llvm.org/D111053
add several patterns that will simplify contraction vectorization in the
future. With those canonicalizationns we will be able to remove the special
case for contration during vectorization and rely on those transformations to
avoid materizalizing broadcast ops.
Differential Revision: https://reviews.llvm.org/D112121
This patch supports the ordered construct in OpenMP dialect following
Section 2.19.9 of the OpenMP 5.1 standard. Also lowering to LLVM IR
using OpenMP IRBduiler. Lowering to LLVM IR for ordered simd directive
is not supported yet since LLVM optimization passes do not support it
for now.
Reviewed By: kiranchandramohan, clementval, ftynse, shraiysh
Differential Revision: https://reviews.llvm.org/D110015
This patch supports the ordered construct in OpenMP dialect following
Section 2.19.9 of the OpenMP 5.1 standard. Also lowering to LLVM IR
using OpenMP IRBduiler. Lowering to LLVM IR for ordered simd directive
is not supported yet since LLVM optimization passes do not support it
for now.
Reviewed By: kiranchandramohan, clementval, ftynse, shraiysh
Differential Revision: https://reviews.llvm.org/D110015
Add a pattern to take a rank-reducing subview and drop inner most
contiguous unit dim.
This is useful when lowering vector to backends with 1d vector types.
Reviewed By: ThomasRaoux
Differential Revision: https://reviews.llvm.org/D111561
According to the OpenMP 5.0 standard, names and hints of critical operation are
closely related. The following are the restrictions on them:
- Unless the effect is as if `hint(omp_sync_hint_none)` was specified, the
critical construct must specify a name.
- If the hint clause is specified, each of the critical constructs with the
same name must have a hint clause for which the hint-expression evaluates to
the same value.
These restrictions will be enforced by design if the hint expression is a part
of the `omp.critical.declare` operation.
- Any operation with no "name" will be considered to have
`hint(omp_sync_hint_none)`.
- All the operations with the same "name" will have the same hint value.
Reviewed By: kiranchandramohan
Differential Revision: https://reviews.llvm.org/D112134
Follow up to also use the prefixed emitters in OpFormatGen (moved
getGetterName(s) and getSetterName(s) to Operator as that is most
convenient usage wise even though it just depends on Dialect). Prefix
accessors in Test dialect and follow up on missed changes in
OpDefinitionsGen.
Differential Revision: https://reviews.llvm.org/D112118
This revision uses the newly refactored StructuredGenerator to create a simple vectorization for conv1d_nwc_wcf.
Note that the pattern is not specific to the op and is technically not even specific to the ConvolutionOpInterface (modulo minor details related to dilations and strides).
The overall design follows the same ideas as the lowering of vector::ContractionOp -> vector::OuterProduct: it seeks to be minimally complex, composable and extensible while avoiding inference analysis. Instead, we metaprogram the maps/indexings we expect and we match against them.
This is just a first stab and still needs to be evaluated for performance.
Other tradeoffs are possible that should be explored.
Reviewed By: ftynse
Differential Revision: https://reviews.llvm.org/D111894
Code reorganized in OpenMPDialect.cpp to have all functions corresponding to an operation together.
Added parseClauses function to avoid code duplication while parsing clauses in OpenMP operations. Also added printers and verifiers for clauses, which are being used for multiple operations.
Reviewed By: kiranchandramohan, peixin
Differential Revision: https://reviews.llvm.org/D110903
The change is based on the proposal from the following discussion:
https://llvm.discourse.group/t/rfc-memreftype-affine-maps-list-vs-single-item/3968
* Introduce `MemRefLayoutAttr` interface to get `AffineMap` from an `Attribute`
(`AffineMapAttr` implements this interface).
* Store layout as a single generic `MemRefLayoutAttr`.
This change removes the affine map composition feature and related API.
Actually, while the `MemRefType` itself supported it, almost none of the upstream
can work with more than 1 affine map in `MemRefType`.
The introduced `MemRefLayoutAttr` allows to re-implement this feature
in a more stable way - via separate attribute class.
Also the interface allows to use different layout representations rather than affine maps.
For example, the described "stride + offset" form, which is currently supported in ASM parser only,
can now be expressed as separate attribute.
Reviewed By: ftynse, bondhugula
Differential Revision: https://reviews.llvm.org/D111553
- `assign` with ArrayRef was calling `append`
- `assign` with empty ArrayRef was not clearing storage
Reviewed By: jpienaar
Differential Revision: https://reviews.llvm.org/D112043
This helper function checks if two given ops are in mutually exclusive branches of the same scf::IfOp.
Differential Revision: https://reviews.llvm.org/D111957
This revison lifts the artificial restriction on having exact matches between
source and destination type shapes. A static size may become dynamic. We still
reject changing a dynamic size into a static size to avoid the need for a
runtime "assert" on the conversion. This revision also refactors some of the
conversion code to share same-content buffers.
Reviewed By: bixia
Differential Revision: https://reviews.llvm.org/D111915
The functionality already exists in AsmParser to parse optional ArrayAttrs and
StringAttrs, but only if they are added to a NamedAttrList. This moves the
code to parse an optional attribute and add it to an list into a common
template, and exposes the simpler functionality of just parsing the optional
attributes.
Reviewed By: rriddle
Differential Revision: https://reviews.llvm.org/D111918
Besides accessing the record, there is currently no way to access all possible
constraint informations, such as the base constraint of a variadic constraint
for example.
Reviewed By: rriddle
Differential Revision: https://reviews.llvm.org/D111719
AnyAttrOf, similar to AnyTypeOf, expects the attribute to be one of the
given attributes.
For instance, `AnyAttrOf<[I32Attr, StrAttr]>` expects either a `I32Attr`,
or a `StrAttr`.
Reviewed By: rriddle
Differential Revision: https://reviews.llvm.org/D111739
This removes edge cases where the default flags we want to use
during printing (e.g. local scope, eliding attributes, etc.)
get missed/dropped.
Differential Revision: https://reviews.llvm.org/D111761
The no-result version of createOrFold calls 'tryFold' but
ignores the result since it doesn't matter what it produced.
Explicitly cast to void to silence this warning:
../llvm/mlir/include/mlir/IR/Builders.h:454:5: warning: ignoring return value of function declared with 'nodiscard' attribute [-Wunused-result]
tryFold(op.getOperation(), unused);
^~~~~~~ ~~~~~~~~~~~~~~~~~~~~~~~~~
Differential Revision: https://reviews.llvm.org/D111951
The existing message hints that the dialect may not be loaded, but there
is also the possibility that the dialect was loaded and the initialize()
method didn't include the Type/Attribute.
This patch removes code very specific to affine dependence analysis and
refactors it as a FlatAfffineRelation.
A FlatAffineRelation represents a set of ordered pairs (domain -> range) where
"domain" and "range" are tuples of identifiers. These relations are used to
represent an "access relation" for memory access on a memref. An access
relation maps elements of an iteration domain to the element(s) of an array
domain accessed by that iteration of the associated statement through some
array reference. The dependence relation representing the dependence
constraints between two memory accesses can be built by composing the access
relation of the destination access by the inverse of the access relation of
source access.
This patch does not change the functionality of the existing dependence
analysis in checkMemrefAccessDependence, but refactors it to use
FlatAffineRelations to deduplicate code and enable code reuse for future
development of features like scheduling, value-based dependence analysis, etc.
Reviewed By: bondhugula
Differential Revision: https://reviews.llvm.org/D110563
Chia-hung Duan