Define IndexExpr before IndexVar. This is to prepare for the next change
to support the use of index values in tensor expressions.
Reviewed By: aartbik
Differential Revision: https://reviews.llvm.org/D121649
When using `--convert-func-to-llvm=emit-c-wrappers` the attribute arguments of the wrapper would not be created correctly in some cases.
This patch fixes that and introduces a set of tests for (hopefully) all corner cases.
See https://github.com/llvm/llvm-project/issues/53503
Author: Sam Carroll <sam.carroll@lmns.com>
Co-Author: Laszlo Kindrat <laszlo.kindrat@lmns.com>
Reviewed By: ftynse
Differential Revision: https://reviews.llvm.org/D119895
Patch adds a new operation for the SIMD construct. The op is designed to be very similar to the existing `wsloop` operation, so that the `CanonicalLoopInfo` of `OpenMPIRBuilder` can be used.
Reviewed By: shraiysh
Differential Revision: https://reviews.llvm.org/D118065
This improves the modularity of the bufferization.
From now on, all ops that do not implement BufferizableOpInterface are considered hoisting barriers. Previously, all ops that do not implement the interface were not considered barriers and such ops had to be marked as barriers explicitly. This was unsafe because we could've hoisted across unknown ops where it was not safe to hoist.
As a side effect, this allows for cleaning up AffineBufferizableOpInterfaceImpl. This build unit no longer needed and can be deleted.
Differential Revision: https://reviews.llvm.org/D121519
Also add a TODO to switch to a custom walk instead of the GreedyPatternRewriter, which should be more efficient. (The bufferization pattern is guaranteed to apply only a single time for every op, so a simple walk should suffice.)
We currently specify a top-to-bottom walk order. This is important because other walk orders could introduce additional casts and/or buffer copies. These canonicalize away again, but it is more efficient to never generate them in the first place.
Note: A few of these canonicalizations are not yet implemented.
Differential Revision: https://reviews.llvm.org/D121518
There is currently an awkwardly complex set of rules for how a
parser/printer is generated for AttrDef/TypeDef. It can change depending on if a
mnemonic was specified, if there are parameters, if using the assemblyFormat, if
individual parser/printer code blocks were specified, etc. This commit refactors
this to make what the attribute/type wants more explicit, and to better align
with how formats are specified for operations.
Firstly, the parser/printer code blocks are removed in favor of a
`hasCustomAssemblyFormat` bit field. This aligns with the operation format
specification (and is nice to remove code blocks from ODS).
This commit also adds a requirement to explicitly set `assemblyFormat` or
`hasCustomAssemblyFormat` when the mnemonic is set and the attr/type
has no parameters. This removes the weird implicit matrix of behavior,
and also encourages the author to make a conscious choice of either C++
or declarative format instead of implicitly opting them into the C++
format (we should be pushing towards declarative when possible).
Differential Revision: https://reviews.llvm.org/D121505
The current documentation is super old, crusty, and at times wrong. This commit
rewrites the documentation to focus on the TableGen declarative definition,
expounds on various components, and moves the doc out of Tutorials/ and into
a new top level `AttributesAndTypes.md` doc. As part of this, the AttrDef/TypeDef
documentation in OpDefinitions.md is removed.
Differential Revision: https://reviews.llvm.org/D120011
OpBase.td has formed into a huge monolith of all ODS constructs. This
commits starts to rectify that by splitting out some constructs to their
own .td files.
Differential Revision: https://reviews.llvm.org/D118636
This patch adds support for custom directives in attribute and type formats. Custom directives dispatch calls to user-defined parser and printer functions.
For example, the assembly format "custom<Foo>($foo, ref($bar))" expects a function with the signature
```
LogicalResult parseFoo(AsmParser &parser, FailureOr<FooT> &foo, BarT bar);
void printFoo(AsmPrinter &printer, FooT foo, BarT bar);
```
Reviewed By: rriddle
Differential Revision: https://reviews.llvm.org/D120944
Implement the vectorLoopUnroll interface for MultiDimReduceOp and add a
pattern to do the unrolling following the same interface other vector
unroll patterns.
Differential Revision: https://reviews.llvm.org/D121263
The revision removes the linalg.fill operation and renames the OpDSL generated linalg.fill_tensor operation to replace it. After the change, all named structured operations are defined via OpDSL and there are no handwritten operations left.
A side-effect of the change is that the pretty printed form changes from:
```
%1 = linalg.fill(%cst, %0) : f32, tensor<?x?xf32> -> tensor<?x?xf32>
```
changes to
```
%1 = linalg.fill ins(%cst : f32) outs(%0 : tensor<?x?xf32>) -> tensor<?x?xf32>
```
Additionally, the builder signature now takes input and output value ranges as it is the case for all other OpDSL operations:
```
rewriter.create<linalg::FillOp>(loc, val, output)
```
changes to
```
rewriter.create<linalg::FillOp>(loc, ValueRange{val}, ValueRange{output})
```
All other changes remain minimal. In particular, the canonicalization patterns are the same and the `value()`, `output()`, and `result()` methods are now implemented by the FillOpInterface.
Depends On D120726
Reviewed By: nicolasvasilache
Differential Revision: https://reviews.llvm.org/D120728
Introduce an explicit `replaceOp` call to enable the tracking of the producer LinalgOp.
Reviewed By: nicolasvasilache
Differential Revision: https://reviews.llvm.org/D121369
This is present since the beginning, but does not seem needed by any
in-tree target right now. This seems like the kind of thing to populate
by the caller if needed.
Differential Revision: https://reviews.llvm.org/D121565
This patch adds supports for union of relations (PresburgerRelation). Along
with this, support for PresburgerSet is also maintained.
This patch is part of a series of patches to add support for relations in
Presburger library.
Reviewed By: arjunp
Differential Revision: https://reviews.llvm.org/D121417
Current generated Python binding for the SCF dialect does not allow
users to call IfOp to create if-else branches on their own.
This PR sets up the default binding generation for scf.if operation
to address this problem.
Reviewed By: ftynse
Differential Revision: https://reviews.llvm.org/D121076
mlir-translate and related tools currently have a fixed set
of flags that are built into Translation.cpp. This works for
simple cases, but some clients want to change the default
globally (e.g. default to allowing unregistered dialects
without a command line flag), or support dialect-independent
translations without having those translations register every
conceivable dialect they could be used with (breaking
modularity).
This approach could also be applied to mlirOptMain to reduce
the significant number of flags it has accumulated.
Differential Revision: https://reviews.llvm.org/D120970
This clarifies that this is an LLVM specific variable and avoids
potential conflicts with other projects.
Differential Revision: https://reviews.llvm.org/D119918
* It doesn't required by OpenCL/Intel Level Zero and can be set programmatically.
* Add GPU to spirv lowering in case when attribute is not present.
* Set higher benefit to WorkGroupSizeConversion pattern so it will always try to lower first from the attribute.
Differential Revision: https://reviews.llvm.org/D120399
Early adoption of new technologies or adjusting certain code generation/IR optimization thresholds
is often available through some cl::opt options (which have unstable surfaces).
Specifying such an option twice will lead to an error.
```
% clang -c a.c -mllvm -disable-binop-extract-shuffle -mllvm -disable-binop-extract-shuffle
clang (LLVM option parsing): for the --disable-binop-extract-shuffle option: may only occur zero or one times!
% clang -c a.c -mllvm -hwasan-instrument-reads=0 -mllvm -hwasan-instrument-reads=0
clang (LLVM option parsing): for the --hwasan-instrument-reads option: may only occur zero or one times!
% clang -c a.c -mllvm --scalar-evolution-max-arith-depth=32 -mllvm --scalar-evolution-max-arith-depth=16
clang (LLVM option parsing): for the --scalar-evolution-max-arith-depth option: may only occur zero or one times!
```
The option is specified twice, because there is sometimes a global setting and
a specific file or project may need to override (or duplicately specify) the
value.
The error is contrary to the common practice of getopt/getopt_long command line
utilities that let the last option win and the `getLastArg` behavior used by
Clang driver options. I have seen such errors for several times. I think the
error just makes users inconvenient, while providing very little value on
discouraging production usage of unstable surfaces (this goal is itself
controversial, because developers might not want to commit to a stable surface
too early, or there is just some subtle codegen toggle which is infeasible to
have a driver option). Therefore, I suggest we drop the diagnostic, at least
before the diagnostic gets sufficiently better support for the overridding needs.
Removing the error is a degraded error checking experience. I think this error
checking behavior, if desirable, should be enabled explicitly by tools. Users
preferring the behavior can figure out a way to do so.
Reviewed By: jhenderson, rnk
Differential Revision: https://reviews.llvm.org/D120455
Add operations -, abs, ceil and floor to the index notation.
Add test cases.
Reviewed By: aartbik
Differential Revision: https://reviews.llvm.org/D121388
In this CL, update the function name of verifier according to the
behavior. If a verifier needs to access the region then it'll be updated
to `verifyRegions`.
Reviewed By: rriddle
Differential Revision: https://reviews.llvm.org/D120373
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
Add operations abs, ceil, floor, and neg to the C++ API and Python API.
Add test cases.
Reviewed By: gysit
Differential Revision: https://reviews.llvm.org/D121339
This patch remove `spaceKind` from PresburgerSpace, making PresburgerSpace only
a space supporting relations.
Sets are still implemented in the same way, i.e. with a zero domain but instead
the asserts to check if the space is still set are added to users of
PresburgerSpace which treat it as a Set space.
Reviewed By: arjunp
Differential Revision: https://reviews.llvm.org/D121357
The enableObjectCache option was added in
https://reviews.llvm.org/rG06e8101034e, defaulting to false. However,
the init code added there got its logic reversed
(cache(enableObjectCache ? nullptr : new SimpleObjectCache()), which was
fixed in https://reviews.llvm.org/rGd1186fcb04 by setting the default to
true, thereby preserving the existing behavior even if it was
unintentional.
Default now the object cache to false as it was originally intended.
While at it, mention in enableObjectCache's documentation how the
cache can be dumped.
Reviewed-by: mehdi_amini
Differential Revision: https://reviews.llvm.org/D121291
This patch moves the testcases from
`mlir/test/Target/LLVMIR/openmp-llvm-bad-schedule-modifier.mlir` to
`mlir/test/Dialect/OpenMP/invalid.mlir` as they test the verifier
(not the translation to LLVM IR).
Reviewed By: NimishMishra
Differential Revision: https://reviews.llvm.org/D120877
On Windows (at least), cmake ignores Python3_EXECUTABLE unless the
'Interpreter' component is being found. If the user is specifying a
different version than the latest installed (say, 3.8 vs 3.9) with the
Python3_EXECUTABLE, cmake was using a combination of the newest version
and the desired version. Mitigated by adding 'Interpreter' in the first
invocation like the second one.
This patch adds lowering from omp.atomic.update to LLVM IR. Whenever a
special LLVM IR instruction is available for the operation, `atomicrmw`
instruction is emitted, otherwise a compare-exchange loop based update
is emitted.
Depends on D119522
Reviewed By: ftynse, peixin
Differential Revision: https://reviews.llvm.org/D119657
When `addCoalescedPolyhedron` was called with `j == n - 1`,
the `polyhedrons`-vector was not properly updated (the
`IntegerPolyhedron` at position `n - 2` was "lost"). This patch adds
special handling to that case and a regression testcase.
Reviewed By: Groverkss
Differential Revision: https://reviews.llvm.org/D121356
This patch moves PresburgerSpace::removeIdRange(idStart, idLimit) to
PresburgerSpace::removeIdRange(kind, idStart, idLimit), i.e. identifiers
can only be removed at once for a single kind.
This makes users of PresburgerSpace to not assume any inside ordering of
identifier kinds.
Reviewed By: arjunp
Differential Revision: https://reviews.llvm.org/D121079
NFC. Clean up memref utils library. This library had a single function
that was completely misplaced. MemRefUtils is expected to be (also per
its comment) a library providing analysis/transforms utilities on memref
dialect ops or memref types. However, in reality it had a helper that
was depended upon by the MemRef dialect, i.e., it was a helper for the
dialect ops library and couldn't contain anything that itself depends on
the MemRef dialect. Move the single method to the memref dialect that
will now allow actual utilities depending on the memref dialect to be
placed in it.
Put findDealloc in the `memref` namespace. This is a pure move.
Differential Revision: https://reviews.llvm.org/D121273
ValueShapeRange::getShape() returns ShapeAdaptor rather than ShapedType
and ShapeAdaptor allows implicit conversion to bool. It ends up that
ShapedTypeComponents can be constructed with ShapeAdaptor incorrectly.
The reason is that the type trait
std::is_constructible<ShapeStorageT, Arg>::value
is fulfilled because ShapeAdaptor can be converted to bool and it can be
used to construct ShapeStorageT. In the end, we won't give any warning
or error message when doing things like
inferredReturnShapes.emplace_back(valueShapeRange.getShape(0));
Reviewed By: jpienaar
Differential Revision: https://reviews.llvm.org/D120845
Currently when we fold an empty loop, we assume that any loop
with iterArgs returns its iterArgs in order, which is not always
the case. It may return values defined outside of the loop or
return its iterArgs out of order. This patch adds support to
those cases.
Reviewed By: dcaballe
Differential Revision: https://reviews.llvm.org/D120776
This revision adds support for the linalg.index to the sparse compiler
pipeline. In essence, this adds the ability to refer to indices in
the tensor index expression, as illustrated below:
Y[i, j, k, l, m] = T[i, j, k, l, m] * i * j
Reviewed By: bixia
Differential Revision: https://reviews.llvm.org/D121251
BuiltinOps.h
These includes are going to be removed from BuiltinOps.h in a followup
when FuncOp is moved out of the Builtin dialect. This commit
pre-emptively adds those includes to simplify the patch moving FuncOp.
It's fine to use any integer (vector) values regardless of the
signedness. The opcode decides how to interpret the bits.
Reviewed By: hanchung
Differential Revision: https://reviews.llvm.org/D121238
This feels like a layering violation, but it fixes the build.
Fixes#54242
tools/mlir/lib/Dialect/GPU/CMakeFiles/obj.MLIRGPUTransforms.dir/Transforms/SerializeToHsaco.cpp.o:SerializeToHsaco.cpp:function (anonymous namespace)::SerializeToHsacoPass::optimizeLlvm(llvm::Module&, llvm::TargetMachine&):
error: undefined reference to 'mlir::makeOptimizingTransformer(unsigned int, unsigned int, llvm::TargetMachine*)'
This pass doesn't rely on any specific characteristics of FuncOp, and
can just be a generic operation pass.
Differential Revision: https://reviews.llvm.org/D121193
It is currently a module pass, but shouldn't be. All of the patterns
are local conversions, and don't require anything about
functions/modules.
Differential Revision: https://reviews.llvm.org/D121192
These passes generally don't rely on any special aspects of FuncOp, and moving allows
for these passes to be used in many more situations. The passes that obviously weren't
relying on invariants guaranteed by a "function" were updated to be generic pass, the
rest were updated to be FunctionOpinterface InterfacePasses.
The test updates are NFC switching from implicit nesting (-pass -pass2) form to
the -pass-pipeline form (generic passes do not implicitly nest as op-specific passes do).
Differential Revision: https://reviews.llvm.org/D121190
FuncOp isn't really important to hardcode here, it is only used to act
as a root operation for the transformation.
Differential Revision: https://reviews.llvm.org/D121195
A lot of test passes are currently anchored on FuncOp, but this
dependency
is generally just historical. A majority of these test passes can run on
any operation, or can operate on a specific interface
(FunctionOpInterface/SymbolOpInterface).
This allows for greatly reducing the API dependency on FuncOp, which
is slated to be moved out of the Builtin dialect.
Differential Revision: https://reviews.llvm.org/D121191
Commit rG1a2bb03edab9d7aa31beb587d0c863acc6715d27 introduced a pattern
to convert dynamic dimensions in operands of `GenericOp`s to static
values based on indexing maps and shapes of other operands. The logic
is directly usable to any `LinalgOp`. Move that pattern as an
`OpInterfaceRewritePattern`.
Differential Revision: https://reviews.llvm.org/D120968
This is a pass that can be used by downstream consumers directly
to avoid the boilerplate to wrap around the `populate*Patterns`.
Reviewed By: ThomasRaoux
Differential Revision: https://reviews.llvm.org/D121222
A `tensor.cast` consumer can be folded with its producer. This is
beneficial only if the result of the tensor cast is more static than
the source. This patch adds a utility function to check that this is
the case, and adds a couple of canonicalizations patterns that fold an
operation with `tensor.cast` conusmers.
Reviewed By: gysit
Differential Revision: https://reviews.llvm.org/D120950
It's valid to create a TypedArrayAttr or MixedContainerType with
nullptr, e.g.,
std::vector<mlir::Attribute> attrs = {mlir::StringAttr()};
builder.createArrayAttr(attrs);
The predicate didn't check if it's a nullptr and it ended up a crash in
the attribute static verifier. We always check if an attribute is null
so it's better to align the check for these two container type attr.
Reviewed By: rdzhabarov
Differential Revision: https://reviews.llvm.org/D121178
With the recent improvements to OpDSL it is cheap to reintroduce a linalg.copy operation.
This operation is needed in at least 2 cases:
1. for copies that may want to change the elemental type (e.g. cast, truncate, quantize, etc)
2. to specify new tensors that should bufferize to a copy operation. The linalg.generic form
always folds away which is not always the right call.
Differential Revision: https://reviews.llvm.org/D121230
Allow pointwise operations to take rank zero input tensors similarly to scalar inputs. Use an empty indexing map to broadcast rank zero tensors to the iteration domain of the operation.
Depends On D120734
Reviewed By: nicolasvasilache
Differential Revision: https://reviews.llvm.org/D120807
The revision removes the SoftPlus2DOp operation that previously served as a test operation. It has been replaced by the elemwise_unary operation, which is now used to test unary log and exp functions.
Reviewed By: nicolasvasilache
Differential Revision: https://reviews.llvm.org/D120794
Simplify tests that use `linalg.fill_rng_2d` to focus on testing the `const` and `index` functions. Additionally, cleanup emit_misc.py to use simpler test functions and fix an error message in config.py.
Reviewed By: nicolasvasilache
Differential Revision: https://reviews.llvm.org/D120734
Extend OpDSL with a `defines` method that can set the `hasCanonicalizer` flag for an OpDSL operation. If the flag is set via `defines(Canonicalizer)` the operation needs to implement the `getCanonicalizationPatterns` method. The revision specifies the flag for linalg.fill_tensor and adds an empty `FillTensorOp::getCanonicalizationPatterns` implementation.
This revision is a preparation step to replace linalg.fill by its OpDSL counterpart linalg.fill_tensor. The two are only functionally equivalent if both specify the same canonicalization patterns. The revision is thus a prerequisite for the linalg.fill replacement.
Depends On D120725
Reviewed By: nicolasvasilache
Differential Revision: https://reviews.llvm.org/D120726
Enhance `LinalgTileAndFuseTensorOpsPattern` with an additional rewrite signature that returns the result of the rewrite.
Reviewed By: nicolasvasilache
Differential Revision: https://reviews.llvm.org/D121212
Add a FillOpInterface similar to the contraction and convolution op interfaces. The FillOpInterface is a preparation step to replace linalg.fill by its OpDSL version linalg.fill_tensor. The interface implements the `value()`, `output()`, and `result()` methods that by default are not available on linalg.fill_tensor.
Reviewed By: nicolasvasilache
Differential Revision: https://reviews.llvm.org/D120725
Currently, the transfer mask is materialized by generating the vector
comparison: [offset + 0, .., offset + length - 1] < [dim, .., dim]
A better alternative is to materialize the transfer mask by using the
operation: `vector.create_mask (dim - offset)`, which will generate
simpler code and compose better with scalable vectors.
Differential Revision: https://reviews.llvm.org/D120487
Rewrite isInnermostAffineForOp utility to make it more direct/efficient.
Drop unnecessary check. NFC.
Differential Revision: https://reviews.llvm.org/D121170
This is to align with the PyTACO API better.
Modify an existing unit test to test the new routines.
Reviewed By: aartbik
Differential Revision: https://reviews.llvm.org/D121083
This patch cleans up the interface to PresburgerSet. At a high level it does
the following changes:
- Move member functions around to have constructors at top and print/dump
at end.
- Move a private function to be a static function instead.
- Change member functions of type "getAllIntegerPolyhedron" to "getAllPolys"
instead.
- Improve documentation for PresburgerSet.
Reviewed By: arjunp
Differential Revision: https://reviews.llvm.org/D121027
In quantized comutation, there are casting ops around computation ops.
Reorder the ops to make reduce-to-contract actually work.
Reviewed By: ThomasRaoux
Differential Revision: https://reviews.llvm.org/D120760
The current StandardToLLVM conversion patterns only really handle
the Func dialect. The pass itself adds patterns for Arithmetic/CFToLLVM, but
those should be/will be split out in a followup. This commit focuses solely
on being an NFC rename.
Aside from the directory change, the pattern and pass creation API have been renamed:
* populateStdToLLVMFuncOpConversionPattern -> populateFuncToLLVMFuncOpConversionPattern
* populateStdToLLVMConversionPatterns -> populateFuncToLLVMConversionPatterns
* createLowerToLLVMPass -> createConvertFuncToLLVMPass
Differential Revision: https://reviews.llvm.org/D120778
These unit tests resides in an internal repository. Porting the tests to the
public repository.
Reviewed By: aartbik
Differential Revision: https://reviews.llvm.org/D121021
The default lowering of vector transpose operations generates a large sequence of
scalar extract/insert operations, one pair for each scalar element in the input tensor.
In other words, the vector transpose is scalarized. However, there are transpose
patterns where one or more adjacent high-order dimensions are not transposed (for
example, in the transpose pattern [1, 0, 2, 3], dimensions 2 and 3 are not transposed).
This patch improves the lowering of those cases by not scalarizing them and extracting/
inserting a full n-D vector, where 'n' is the number of adjacent high-order dimensions
not being transposed. By doing so, we prevent the scalarization of the code and generate a
more performant vector version.
Paradoxically, this patch shouldn't improve the performance of transpose operations if
we are using LLVM. The LLVM pipeline is able to optimize away some of the extract/insert
operations and the SLP vectorizer is converting the scalar operations back to its vector
form. However, scalarizing a vector version of the code in MLIR and relying on the SLP
vectorizer to reconstruct the vector code again is highly undesirable for several reasons.
Reviewed By: nicolasvasilache, ThomasRaoux
Differential Revision: https://reviews.llvm.org/D120601
This patch fixes the crash when printing some ops (like affine.for and
scf.for) when they are dumped in invalid state, e.g. during pattern
application. Now the AsmState constructor verifies the operation
first and switches to generic operation printing when the verification
fails. Also operations are now printed in generic form when emitting
diagnostics and the severity level is Error.
Reviewed By: rriddle, mehdi_amini
Differential Revision: https://reviews.llvm.org/D117834
Translation.h is currently awkwardly shoved into the top-level mlir, even though it is
specific to the mlir-translate tool. This commit moves it to a new Tools/mlir-translate
directory, which is intended for libraries used to implement tools. It also splits the
translate registry from the main entry point, to more closely mirror what mlir-opt
does.
Differential Revision: https://reviews.llvm.org/D121026
MlirOptMain is currently awkwardly shoved into mlir/Support. This commit
moves it to the Tools/ directory, which is intended for libraries used to
implement tools.
Differential Revision: https://reviews.llvm.org/D121025
There is no reason for this file to be at the top-level, and
its current placement predates the Parser/ folder's existence.
Differential Revision: https://reviews.llvm.org/D121024
Mark `parseSourceFile()` deprecated. The functions will be removed two weeks after landing this change.
Reviewed By: rriddle
Differential Revision: https://reviews.llvm.org/D121075
The OpenMPIRBuilder has a bug. Specifically, suppose you have two nested openmp parallel regions (writing with MLIR for ease)
```
omp.parallel {
%a = ...
omp.parallel {
use(%a)
}
}
```
As OpenMP only permits pointer-like inputs, the builder will wrap all of the inputs into a stack allocation, and then pass this
allocation to the inner parallel. For example, we would want to get something like the following:
```
omp.parallel {
%a = ...
%tmp = alloc
store %tmp[] = %a
kmpc_fork(outlined, %tmp)
}
```
However, in practice, this is not what currently occurs in the context of nested parallel regions. Specifically to the OpenMPIRBuilder,
the entirety of the function (at the LLVM level) is currently inlined with blocks marking the corresponding start and end of each
region.
```
entry:
...
parallel1:
%a = ...
...
parallel2:
use(%a)
...
endparallel2:
...
endparallel1:
...
```
When the allocation is inserted, it presently inserted into the parent of the entire function (e.g. entry) rather than the parent
allocation scope to the function being outlined. If we were outlining parallel2, the corresponding alloca location would be parallel1.
This causes a variety of bugs, including https://github.com/llvm/llvm-project/issues/54165 as one example.
This PR allows the stack allocation to be created at the correct allocation block, and thus remedies such issues.
Reviewed By: jdoerfert
Differential Revision: https://reviews.llvm.org/D121061
This commit adds a new hook Pass `bool canScheduleOn(RegisteredOperationName)` that
indicates if the given pass can be scheduled on operations of the given type. This makes it
easier to define constraints on generic passes without a) adding conditional checks to
the beginning of the `runOnOperation`, or b) defining a new pass type that forwards
from `runOnOperation` (after checking the invariants) to a new hook. This new hook is
used to implement an `InterfacePass` pass class, that represents a generic pass that
runs on operations of the given interface type.
The PassManager will also verify that passes added to a pass manager can actually be
scheduled on that pass manager, meaning that we will properly error when an Interface
is scheduled on an operation that doesn't actually implement that interface.
Differential Revision: https://reviews.llvm.org/D120791
RegionBranchOpInterface and BranchOpInterface are allowed to make implicit type conversions along control-flow edges. In effect, this adds an interface method, `areTypesCompatible`, to both interfaces, which should return whether the types of corresponding successor operands and block arguments are compatible. Users of the interfaces, here on forth, must be aware that types may mismatch, although current users (in MLIR core), are not affected by this change. By default, type equality is used.
`async.execute` already has unequal types along control-flow edges (`!async.value<f32>` vs. `f32`), but it opted out of calling `RegionBranchOpInterface::verifyTypes` in its verifier. That method has now been removed and `RegionBranchOpInterface` will verify types along control edges by default in its verifier.
Reviewed By: rriddle
Differential Revision: https://reviews.llvm.org/D120790
Such initializer functions can be enqueued in `BufferizationOptions`. They can be used to set up dialect-specific bufferization state.
Differential Revision: https://reviews.llvm.org/D120985
This clarifies that these methods only work in append mode, not for general insertions. This is a prospective change towards https://github.com/llvm/llvm-project/issues/51652 which also performs random-access insertions, so we want to avoid confusion.
Reviewed By: aartbik
Differential Revision: https://reviews.llvm.org/D120929
This patch extends the existing if combining canonicalization to also handle the case where a value returned by the first if is used within the body of the second if.
This patch also extends if combining to support if's whose conditions are logical negations of each other.
Reviewed By: ftynse
Differential Revision: https://reviews.llvm.org/D120924
This patch makes coalesce skip the comparison of all pairs of IntegerPolyhedrons with LocalIds rather than crash. The heuristics to handle these cases will be upstreamed later on.
Reviewed By: arjunp
Differential Revision: https://reviews.llvm.org/D120995
We can simplify an extractvalue of an insertvalue to extract out of the base of the insertvalue, if the insert and extract are at distinct and non-prefix'd indices
Reviewed By: ftynse
Differential Revision: https://reviews.llvm.org/D120915
This patch introduces the cut case. If one polytope has only cutting and
redundant inequalities for the other and the facet of the cutting
inequalities are contained within the other polytope, then the polytopes are
be combined into a polytope consisting only of their respective
redundant constraints.
Reviewed By: arjunp
Differential Revision: https://reviews.llvm.org/D120614
Extend isLoopMemoryParallel check to include locally allocated memrefs.
This strengthens and also speeds up the dependence check used by the
utility by excluding locally allocated memrefs where appropriate.
Additional memref dialect ops can be supported exhaustively via proper
interfaces.
Reviewed By: dcaballe
Differential Revision: https://reviews.llvm.org/D120617
An OpenMP wsloop is simply a regular for loop with the bounds determined by the thread number, and the same justification to allow this for scf.for works for omp.wsloop.
An OpenMP parallel is a parallel for, per thread. Similarly the same justification for scf.parallel having recursive side effects applies here.
In both cases the general justification is that the ops themselves don't have side effects (besides inaccessible runtime-specific memory) and thus the side effects are simply that of the contained ops.
Reviewed By: bondhugula
Differential Revision: https://reviews.llvm.org/D120853
This commit adds support for processing tablegen include files, and importing
various information from ODS. This includes operations, attribute+type constraints,
attribute/operation/type interfaces, etc. This will allow for much more robust tooling,
and also allows for referencing ODS constructs directly within PDLL (imported interfaces
can be used as constraints, operation result names can be used for member access, etc).
Differential Revision: https://reviews.llvm.org/D119900
The SerializeToHsaco pass does not depend on ROCm being available on
the build system - it only requires ROCm to be present at runtime.
However, the CMake file that built it tested for
MLIR_ENABLE_ROCM_RUNNER , which implies that ROCm is currently
available and is used to control building ROCm integration tests.
Referencing MLIR_ENABLE_ROCM_RUNNER instead of
MLIR_ENABLE_ROCM_CONVERSIONS in the SerializeToHsaco build therefore
causes problems for clients who wish to build projects that depend on
this pass on a system without an AMD GPU present.
Reviewed By: whchung
Differential Revision: https://reviews.llvm.org/D120663
Ensure that `Handler` within the class is interpreted as the as the current template instantiation (instead the class template itself).
Fixes#53447
Reviewed By: rriddle
Differential Revision: https://reviews.llvm.org/D120852
This ensures that we generate memref types with matching layout maps. (Especially when using partial bufferization passes.)
Differential Revision: https://reviews.llvm.org/D120893
This commit deletes the old dialect conversion-based bufferization patterns, which are now obsolete.
Differential Revision: https://reviews.llvm.org/D120883
The loopInfos gets invalidated after collapsing nested loops. Use the
saved afterIP since the returned afterIP by applyDynamicWorkshareLoop
may be not valid.
Reviewed By: shraiysh
Differential Revision: https://reviews.llvm.org/D120294
StandardToSPIRV currently contains an assortment of patterns converting from
different dialects to SPIRV. This commit splits up StandardToSPIRV into separate
conversions for each of the dialects involved (some of which already exist).
Differential Revision: https://reviews.llvm.org/D120767
Add support for extensible dialects, which are dialects that can be
extended at runtime with new operations and types.
These operations and types cannot at the moment implement traits
or interfaces.
Differential Revision: https://reviews.llvm.org/D104554
LLVM defines several default datalayouts for integer and floating point types that are not being considered when importing into MLIR. This patch remedies this.
Reviewed By: ftynse
Differential Revision: https://reviews.llvm.org/D120832
https://reviews.llvm.org/D120423 replaced the use of stacksave/restore with memref.alloca_scope, but kept the save/restore at the same location. This PR places the allocation scope within the wsloop, thus keeping the same allocation scope as the original scf.parallel (e.g. no longer over stack allocating).
Reviewed By: ftynse
Differential Revision: https://reviews.llvm.org/D120772
This patch moves all functionality from IntegerPolyhedron to IntegerRelation.
IntegerPolyhedron is now implemented as a relation with no domain. All existing
functionality is extended to work on relations.
This patch does not affect external users like FlatAffineConstraints as they
can still continue to use IntegerPolyhedron abstraction.
This patch is part of a series of patches to support relations in Presburger
library.
Reviewed By: arjunp
Differential Revision: https://reviews.llvm.org/D120652
Add support for translating data layout specifications for integer and float
types between MLIR and LLVM IR. This is a first step towards removing the
string-based LLVM dialect data layout attribute on modules. The latter is still
available and will remain so until the first-class MLIR modeling can fully
replace it.
Depends On D120739
Reviewed By: wsmoses
Differential Revision: https://reviews.llvm.org/D120740
Add support for integer and float types into the data layout subsystem with
default logic similar to LLVM IR. Given the flexibility of the sybsystem, the
logic can be easily overwritten by operations if necessary. This provides the
connection necessary, e.g., for the GPU target where alignment requirements for
integers and floats differ from those provided by default (although still
compatible with the LLVM IR model). Previously, it was impossible to use
non-default alignment requirements for integer and float types, which could
lead to incorrect address and size calculations when targeting GPUs.
Depends On D120737
Reviewed By: wsmoses
Differential Revision: https://reviews.llvm.org/D120739
This patch adds assemblyFormat for `omp.critical.declare`, `omp.atomic.read`,
`omp.atomic.write`, `omp.atomic.update` and `omp.atomic.capture`.
Also removing those clauses from `parseClauses` that aren't needed
anymore, thanks to the new assemblyFormats.
Reviewed By: NimishMishra, rriddle
Differential Revision: https://reviews.llvm.org/D120248
sparsity values.
Previously, we can't properly handle input tensors with a dimension
ordering that is different from the natural ordering or with a mixed of
compressed and dense dimensions. This change fixes the problems by
passing the dimension ordering and sparsity values to the runtime
routine.
Modify an existing test to test the situation.
Reviewed By: aartbik
Differential Revision: https://reviews.llvm.org/D120777
This adds an option to configure the CMake python search priming
behaviour that was introduced in D118148. In some environments the
priming would cause the "real" search to fail. The default behaviour is
unchanged, i.e. the search will be primed.
Reviewed By: stellaraccident
Differential Revision: https://reviews.llvm.org/D120765
The remanants of Standard was renamed to Func, but the test directory
remained named as Standard. In adidition to fixing the name, this commit
also moves the tests for operations not in the Func dialect to the proper
parent dialect test directory.
The Func has a large number of legacy dependencies carried over from the old
Standard dialect, which was pervasive and contained a large number of varied
operations. With the split of the standard dialect and its demise, a lot of lingering
dead dependencies have survived to the Func dialect. This commit removes a
large majority of then, greatly reducing the dependence surface area of the
Func dialect.
The last remaining operations in the standard dialect all revolve around
FuncOp/function related constructs. This patch simply handles the initial
renaming (which by itself is already huge), but there are a large number
of cleanups unlocked/necessary afterwards:
* Removing a bunch of unnecessary dependencies on Func
* Cleaning up the From/ToStandard conversion passes
* Preparing for the move of FuncOp to the Func dialect
See the discussion at https://discourse.llvm.org/t/standard-dialect-the-final-chapter/6061
Differential Revision: https://reviews.llvm.org/D120624
Previously, convertToMLIRSparseTensor assumes identity storage ordering and all
compressed dimensions. This change extends the function with two parameters for
users to specify the storage ordering and the sparsity of each dimension.
Modify PyTACO to reflect this change.
Reviewed By: aartbik
Differential Revision: https://reviews.llvm.org/D120643
As discussed in https://reviews.llvm.org/D119743 scf.parallel would continuously stack allocate since the alloca op was placd in the wsloop rather than the omp.parallel. This PR is the second stage of the fix for that problem. Specifically, we now introduce an alloca scope around the inlined body of the scf.parallel and enable a canonicalization to hoist the allocations to the surrounding allocation scope (e.g. omp.parallel).
Reviewed By: ftynse
Differential Revision: https://reviews.llvm.org/D120423
The llvm.mlir.global operation accepts a region as initializer. This region
corresponds to an LLVM IR constant expression and therefore should not accept
operations with side effects. Add a corresponding verifier.
Reviewed By: wsmoses, bondhugula
Differential Revision: https://reviews.llvm.org/D120632
The revision renames the following OpDSL functions:
```
TypeFn.cast -> TypeFn.cast_signed
BinaryFn.min -> BinaryFn.min_signed
BinaryFn.max -> BinaryFn.max_signed
```
The corresponding enum values on the C++ side are renamed accordingly:
```
#linalg.type_fn<cast> -> #linalg.type_fn<cast_signed>
#linalg.binary_fn<min> -> #linalg.binary_fn<min_signed>
#linalg.binary_fn<max> -> #linalg.binary_fn<max_signed>
```
Depends On D120110
Reviewed By: aartbik
Differential Revision: https://reviews.llvm.org/D120562
The revision extends OpDSL with unary and binary function attributes. A function attribute, makes the operations used in the body of a structured operation configurable. For example, a pooling operation may take an aggregation function attribute that specifies if the op shall implement a min or a max pooling. The goal of this revision is to define less and more flexible operations.
We may thus for example define an element wise op:
```
linalg.elem(lhs, rhs, outs=[out], op=BinaryFn.mul)
```
If the op argument is not set the default operation is used.
Depends On D120109
Reviewed By: nicolasvasilache, aartbik
Differential Revision: https://reviews.llvm.org/D120110
Add applyStaticChunkedWorkshareLoop method implementing static schedule when chunk-size is specified. Unlike a static schedule without chunk-size (where chunk-size is chosen by the runtime such that each thread receives one chunk), we need two nested loops: one for looping over the iterations of a chunk, and a second for looping over all chunks assigned to the threads.
This patch includes the following related changes:
* Adapt applyWorkshareLoop to triage between the schedule types, now possible since all schedules have been implemented. The default schedule is assumed to be non-chunked static, as without OpenMPIRBuilder.
* Remove the chunk parameter from applyStaticWorkshareLoop, it is ignored by the runtime. Change the value for the value passed to the init function to 0, as without OpenMPIRBuilder.
* Refactor CanonicalLoopInfo::setTripCount and CanonicalLoopInfo::mapIndVar as used by both, applyStaticWorkshareLoop and applyStaticChunkedWorkshareLoop.
* Enable Clang to use the OpenMPIRBuilder in the presence of the schedule clause.
Differential Revision: https://reviews.llvm.org/D114413
Add a pattern matcher for ExtractSliceOp when its source is a constant.
The matching heuristics can be governed by the control function since
generating a new constant is not always beneficial.
Differential Revision: https://reviews.llvm.org/D119605
If we have a chain of `tensor.insert_slice` ops inserting some
`tensor.pad` op into a `linalg.fill` and ranges do not overlap,
we can also elide the `tensor.pad` later.
Reviewed By: ThomasRaoux
Differential Revision: https://reviews.llvm.org/D120446
Fold tensor.insert_slice(tensor.pad(<input>), linalg.fill) into
tensor.insert_slice(<input>, linalg.fill) if the padding value and
the filling value are the same.
Reviewed By: ThomasRaoux
Differential Revision: https://reviews.llvm.org/D120410
Improve the LinalgOp verification to ensure the iterator types is known. Previously, unknown iterator types have been ignored without warning, which can lead to confusing bugs.
Reviewed By: nicolasvasilache
Differential Revision: https://reviews.llvm.org/D120649
This patch removes the builders for `omp.wsloop` operation that aren't
specifically needed anywhere. We can add them later if the need arises.
Reviewed By: kiranchandramohan
Differential Revision: https://reviews.llvm.org/D120533
This patch moves IntegerPolyhedron::reset to FlatAffineConstraints::reset. This
function is not required in IntegerPolyhedron and creates ambiguity while
shifting implementations to IntegerRelation.
This patch is part of a series of patches to introduce relations in Presburger
library.
Reviewed By: arjunp
Differential Revision: https://reviews.llvm.org/D120628
PDL currently doesn't support result values from constraints, meaning we need
to error out until this is actually supported to avoid crashes.
Differential Revision: https://reviews.llvm.org/D119782
This commits adds a C++ generator to PDLL that generates wrapper PDL patterns
directly usable in C++ code, and also generates the definitions of native constraints/rewrites
that have code bodies specified in PDLL. This generator is effectively the PDLL equivalent of
the current DRR generator, and will allow easy replacement of DRR patterns with PDLL patterns.
A followup will start to utilize this for end-to-end integration testing and show case how to
use this as a drop-in replacement for DRR tablegen usage.
Differential Revision: https://reviews.llvm.org/D119781
If the operand list or result list of an operation expression is not specified, we interpret
this as meaning that the operands/results are "unconstraint" (i.e. "could be anything").
We currently don't properly handle differentiating this case from the case of
"no operands/results". This commit adds the insertion of implicit value/type range
variables when these lists are unspecified. This allows for adding proper support
for when zero operands or results are expected.
Differential Revision: https://reviews.llvm.org/D119780
This commits starts to plumb PDLL down into MLIR and adds an initial
PDL generator. After this commit, we will have conceptually support
end-to-end execution of PDLL. Followups will add CPP generation to
match the current DRR setup, and begin to add various end-to-end
tests to test PDLL execution.
Differential Revision: https://reviews.llvm.org/D119779
This patch removes a redundant check in hasConsistentState which is always true
after introduction of PresburgerSpace.
Reviewed By: arjunp
Differential Revision: https://reviews.llvm.org/D120615
This patch moves identifier kind specific insert/append functions like
`insertDimId`, `appendSymbolId`, etc. from IntegerPolyhedron to
FlatAffineConstraints.
This change allows for a smoother transition to IntegerRelation.
This change is part of a series of patches to introduce Relations in Presburger
library.
Reviewed By: arjunp
Differential Revision: https://reviews.llvm.org/D120576
This patch factors out various checks for dimension compatibility to
PresburgerSpace::isEqual and PresburgerLocalSpace::isEqual (for local
identifiers).
Reviewed By: arjunp
Differential Revision: https://reviews.llvm.org/D120565
In the main-loop of the current coalesce implementation `i` was incremented
twice for some cases. This patch fixes this bug and adds a regression
testcase.
Reviewed By: arjunp
Differential Revision: https://reviews.llvm.org/D120613
The PyTACO DSL doesn't support reduction to scalars. This change
enhances the MLIR-PyTACO implementation to support reduction to scalars.
Extend an existing test to show the syntax of reduction to scalars and
two methods to retrieve the scalar values.
Reviewed By: aartbik
Differential Revision: https://reviews.llvm.org/D120572
The AVX2 lowering for transpose operations is only applicable to f32 vector types.
Reviewed By: aartbik
Differential Revision: https://reviews.llvm.org/D120427
The existing AVX2 lowering patterns for the transpose op only triggers if the
input vector is 2-D. This patch extends the patterns to trigger for n-D vectors
which are effectively 2-D vectors (e.g., vector<1x4x1x8x1). The main constraint
for the generalized AVX2 patterns to be applicable to these vectors is that the
dimensions that are greater than one must be transposed. Otherwise, the existing
patterns are not applicable.
Reviewed By: nicolasvasilache
Differential Revision: https://reviews.llvm.org/D119505
This change gives explicit order of verifier execution and adds
`hasRegionVerifier` and `verifyWithRegions` to increase the granularity
of verifier classification. The orders are as below,
1. InternalOpTrait will be verified first, they can be run independently.
2. `verifyInvariants` which is constructed by ODS, it verifies the type,
attributes, .etc.
3. Other Traits/Interfaces that have marked their verifier as
`verifyTrait` or `verifyWithRegions=0`.
4. Custom verifier which is defined in the op and has marked
`hasVerifier=1`
If an operation has regions, then it may have the second phase,
5. Traits/Interfaces that have marked their verifier as
`verifyRegionTrait` or
`verifyWithRegions=1`. This implies the verifier needs to access the
operations in its regions.
6. Custom verifier which is defined in the op and has marked
`hasRegionVerifier=1`
Note that the second phase will be run after the operations in the
region are verified. Based on the verification order, you will be able to
avoid verifying duplicate things.
Reviewed By: Mogball
Differential Revision: https://reviews.llvm.org/D116789
Fix MLIR-PyTACO and some tests to use np.array_equal to compare integer
values.
Reviewed By: aartbik
Differential Revision: https://reviews.llvm.org/D120526
Split arithmetic function into unary and binary functions. The revision prepares the introduction of unary and binary function attributes that work similar to type function attributes.
Depends On D120108
Reviewed By: aartbik
Differential Revision: https://reviews.llvm.org/D120109
This change allows the use of scalar tensors with index 0 in tensor index
expressions. In this case, the scalar value is broadcast to match the
dimensions of other tensors in the same expression.
Using scalar tensors as a destination in tensor index expressions is not
supported in the PyTACO DSL.
Add a PyTACO test to show the use of scalar tensors.
Reviewed By: aartbik
Differential Revision: https://reviews.llvm.org/D120524
Prepare the OpDSL function handling to introduce more function classes. A follow up commit will split ArithFn into UnaryFn and BinaryFn. This revision prepares the split by adding a function kind enum to handle different function types using a single class on the various levels of the stack (for example, there is now one TensorFn and one ScalarFn).
Depends On D119718
Reviewed By: aartbik
Differential Revision: https://reviews.llvm.org/D120108
This patch refactors the looping strategy of coalesce for future patches. The new strategy works in-place and uses IneqType to organize inequalities into vectors of the same type. Future coalesce cases will pattern match on this organization. E.g. the contained case needs all inequalities and equalities to be redundant, so this case becomes checking whether the respective vectors are empty. For other cases, the patterns consider the types of all inequalities of both sets making it wasteful to only consider whether a can be coalesced with b in one step, as inequalities would need to be typed again for the opposite case. Therefore, the new strategy tries to coalesce a with b and b with a in a single step.
Reviewed By: Groverkss, arjunp
Differential Revision: https://reviews.llvm.org/D120392
This patch replaces various functions over inequalities/equalities in
IntegerPolyhedron with Matrix functions already implementing them or refactors
them to a Matrix function.
Reviewed By: arjunp
Differential Revision: https://reviews.llvm.org/D120482
This patch moves the Presburger library to a new `presburger` namespace.
This allows to shorten some names, helps to avoid polluting the mlir namespace,
and also provides some structure.
Reviewed By: arjunp
Differential Revision: https://reviews.llvm.org/D120505
This patch removes redundant code from fourierMotzkinEliminate implementation
using existing functions in IntegerPolyhedron.
Reviewed By: arjunp
Differential Revision: https://reviews.llvm.org/D120502
Previously, OpDSL operation used hardcoded type conversion operations (cast or cast_unsigned). Supporting signed and unsigned casts thus meant implementing two different operations. Type function attributes allow us to define a single operation that has a cast type function attribute which at operation instantiation time may be set to cast or cast_unsigned. We may for example, defina a matmul operation with a cast argument:
```
@linalg_structured_op
def matmul(A=TensorDef(T1, S.M, S.K), B=TensorDef(T2, S.K, S.N), C=TensorDef(U, S.M, S.N, output=True),
cast=TypeFnAttrDef(default=TypeFn.cast)):
C[D.m, D.n] += cast(U, A[D.m, D.k]) * cast(U, B[D.k, D.n])
```
When instantiating the operation the attribute may be set to the desired cast function:
```
linalg.matmul(lhs, rhs, outs=[out], cast=TypeFn.cast_unsigned)
```
The revsion introduces a enum in the Linalg dialect that maps one-by-one to the type functions defined by OpDSL.
Reviewed By: aartbik
Differential Revision: https://reviews.llvm.org/D119718
This patch removes the `const` from `usingBigM` to enable the implicit copy assignment operator for Simplex.
Reviewed By: Groverkss
Differential Revision: https://reviews.llvm.org/D120542
This transformation is useful to break dependency between consecutive loop
iterations by increasing the size of a temporary buffer. This is usually
combined with heavy software pipelining.
Differential Revision: https://reviews.llvm.org/D119406
This adds a variable op, emitted as C/C++ locale variable, which can be
used if the `emitc.constant` op is not sufficient.
As an example, the canonicalization pass would transform
```mlir
%0 = "emitc.constant"() {value = 0 : i32} : () -> i32
%1 = "emitc.constant"() {value = 0 : i32} : () -> i32
%2 = emitc.apply "&"(%0) : (i32) -> !emitc.ptr<i32>
%3 = emitc.apply "&"(%1) : (i32) -> !emitc.ptr<i32>
emitc.call "write"(%2, %3) : (!emitc.ptr<i32>, !emitc.ptr<i32>) -> ()
```
into
```mlir
%0 = "emitc.constant"() {value = 0 : i32} : () -> i32
%1 = emitc.apply "&"(%0) : (i32) -> !emitc.ptr<i32>
%2 = emitc.apply "&"(%0) : (i32) -> !emitc.ptr<i32>
emitc.call "write"(%1, %2) : (!emitc.ptr<i32>, !emitc.ptr<i32>) -> ()
```
resulting in pointer aliasing, as %1 and %2 point to the same address.
In such a case, the `emitc.variable` operation can be used instead.
Reviewed By: jpienaar
Differential Revision: https://reviews.llvm.org/D120098
This patch removes binary operator enum which was introduced with `omp.atomic.update`. Now the update operation handles update in a region so this is no longer required.
Reviewed By: kiranchandramohan
Differential Revision: https://reviews.llvm.org/D120458
Documentation exists about the details of the API but is missing a
description of the overall structure per dialect.
Reviewed By: shabalin
Differential Revision: https://reviews.llvm.org/D117002
The current implementation of ShuffleVectorOp assumes all vectors are
scalable. LLVM IR allows shufflevector operations on scalable vectors,
and the current translation between LLVM Dialect and LLVM IR does the
rigth thing when the shuffle mask is all zeroes. This is required to
do a splat operation on a scalable vector, but it doesn't make sense
for scalable vectors outside of that operation, i.e.: with non-all zero
masks.
Differential Revision: https://reviews.llvm.org/D118371
In D115022, we introduced an optimization where OpResults of a `linalg.generic` may bufferize in-place with an "in" OpOperand if the corresponding "out" OpOperand is not used in the computation.
This optimization can lead to unexpected behavior if the newly chosen OpOperand is in the same alias set as another OpOperand (that is used in the computation). In that case, the newly chosen OpOperand must bufferize out-of-place. This can be confusing to users, as always choosing the "out" OpOperand (regardless of whether it is used) would be expected when having the notion of "destination-passing style" in mind.
With this change, we go back to always bufferizing in-place with "out" OpOperands by default, but letting users override the behavior with a bufferization option.
Differential Revision: https://reviews.llvm.org/D120182
Previously only accessing values for `index` and signless int types
would work; signed and unsigned ints would hit an assert in
`IntegerAttr::getInt`. This exposes `IntegerAttr::get{S,U}Int` to the C
API and calls the appropriate function from the python bindings.
Reviewed By: ftynse
Differential Revision: https://reviews.llvm.org/D120194
Previously, we only support float64. We now support float32 and float64. When
constructing a tensor without providing a data type, the default is float32.
Fix the tests to data type consistency. All PyTACO application tests now use
float32 to match the default data type of TACO. Other tests may use float32 or
float64.
Reviewed By: aartbik
Differential Revision: https://reviews.llvm.org/D120356
Now that sparse tensor types are first-class citizens and the sparse compiler
is taking shape, it is time to make sure other compiler optimizations compose
well with sparse tensors. Mostly, this should be completely transparent (i.e.,
dense and sparse take the same path). However, in some cases, optimizations
only make sense in the context of sparse tensors. This is a first example of
such an optimization, where fusing a sampled elt-wise multiplication only makes
sense when the resulting kernel has a potential lower asymptotic complexity due
to the sparsity.
As an extreme example, running SDDMM with 1024x1024 matrices and a sparse
sampling matrix with only two elements runs in 463.55ms in the unfused
case but just 0.032ms in the fused case, with a speedup of 14485x that
is only possible in the exciting world of sparse computations!
Reviewed By: mravishankar
Differential Revision: https://reviews.llvm.org/D120429
By specifying a sectionMemoryMapper, users can control how
memory for JIT code is allocated.
In particular, I need this in order to use a named memory
region so that profilers such as perf(1) can correctly label
execution cycles coming from JIT'ed code.
Reviewed-by: ezhulenev
Differential Revision: https://reviews.llvm.org/D120415
Given a cmpf of either uitofp or sitofp and a constant, attempt to canonicalize it to a cmpi.
This PR rewrites equivalent code within LLVM to now apply to MLIR arith.
Reviewed By: rriddle
Differential Revision: https://reviews.llvm.org/D117257
+ compare block size with the unrollable inner dimension
+ reduce nesting in the code and simplify a bit IR building
Reviewed By: cota
Differential Revision: https://reviews.llvm.org/D120075
This eliminates the requirement that pass-related strings outlive pass
instances, which will facilitate future work enabling dynamic passes
written in other languages.
Differential Revision: https://reviews.llvm.org/D120341
Its number of optional parameters has grown too large,
which makes adding new optional parameters quite a chore.
Fix this by using an options struct.
Reviewed By: mehdi_amini
Differential Revision: https://reviews.llvm.org/D120380
Use an `MLIRContext` declared in a single place in the `parsePoly` function that almost all Presburger unit tests use for parsing sets. This function is only used in tests.
This saves us from having to declare and pass a new `MLIRContext` in every test.
Reviewed By: bondhugula, mehdi_amini
Differential Revision: https://reviews.llvm.org/D119251
This trait results in PDL ops being erroneously CSE'd. These ops are side-effect free in the rewriter but not in the matcher (where unused values aren't allowed anyways). These ops should have a more nuanced side-effect modeling, this is fixing a bug introduced by a previous change.
Reviewed By: rriddle
Differential Revision: https://reviews.llvm.org/D120222
Header class in SPIR-V HTML spec has changed. Update script to reflect that.
Reviewed By: antiagainst
Differential Revision: https://reviews.llvm.org/D120179
The related functionality is moved over to the bufferization dialect. Test cases are cleaned up a bit.
Differential Revision: https://reviews.llvm.org/D120191
Aart Bik