This patch adds support for checking if two PresburgerSets are equal. In particular, one can check if two FlatAffineConstraints are equal by constructing PrebsurgerSets from them and comparing these.
Reviewed By: ftynse
Differential Revision: https://reviews.llvm.org/D94915
Use cross-compilation approach for `mlir-linalg-ods-gen` application
similar to TblGen tools.
Reviewed By: nicolasvasilache
Differential Revision: https://reviews.llvm.org/D94598
Added the ability to read (an extended version of) the FROSTT
file format, so that we can now read in sparse tensors of arbitrary
rank. Generalized the API to deal with more than two dimensions.
Also added the ability to sort the indices of sparse tensors
lexicographically. This is an important step towards supporting
auto gen of initialization code, since sparse storage formats
are easier to initialize if the indices are sorted. Since most
external formats don't enforce such properties, it is convenient
to have this ability in our runtime support library.
Lastly, the re-entrant problem of the original implementation
is fixed by passing an opaque object around (rather than having
a single static variable, ugh!).
Reviewed By: nicolasvasilache
Differential Revision: https://reviews.llvm.org/D94852
The operantion is an identity if the values yielded by the operation
is the argument of the basic block of that operation. Add this missing check.
Differential Revision: https://reviews.llvm.org/D94819
This commit adds support to generate an additional builder for
each named op that has attributes. This gives better experience
when creating the named ops.
Along the way adds support for i64.
Reviewed By: hanchung
Differential Revision: https://reviews.llvm.org/D94733
This is a very minor improvement during iteration graph construction.
If the first attempt considering the dimension order of all tensors fails,
a second attempt is made using the constraints of sparse tensors only.
Dense tensors prefer dimension order (locality) but provide random access
if needed, enabling the compilation of more sparse kernels.
Reviewed By: penpornk
Differential Revision: https://reviews.llvm.org/D94709
With the recent changes to linalg on tensor semantics, the tiling
operations works out-of-the-box for generic operations. Add a test to
verify that and some minor refactoring.
Differential Revision: https://reviews.llvm.org/D93077
Add canonicalization to replace use of the result of a linalg
operation on tensors in a dim operation, to use one of the operands of
the linalg operations instead. This allows the linalg op itself to be
deleted when all its non-dim uses are removed (say through tiling, etc.)
Differential Revision: https://reviews.llvm.org/D93076
linalg.generic/indexed_generic operations on tensors whose body is
just yielding the (non-induction variable) arguments of the operation
can be canonicalized by replacing uses of the result with the
corresponding arguments.
Differential Revision: https://reviews.llvm.org/D94581
The standard and gpu dialect both have `alloc` operations which use the
memory effect `MemAlloc`. In both cases, it is specified on both the
operation itself and on the result. This results in two memory effects
being created for these operations. When `MemAlloc` is defined on an
operation, it represents some background effect which the compiler
cannot reason about, and inhibits the ability of the compiler to
remove dead `std.alloc` operations. This change removes the uneeded
`MemAlloc` effect from these operations and leaves the effect on the
result, which allows dead allocs to be erased.
There is the same problem, but to a lesser extent, with MemFree, MemRead
and MemWrite. Over-specifying these traits is not currently inhibiting
any optimization.
Differential Revision: https://reviews.llvm.org/D94662
This spilts out BufferDeallocationInternals.md, since buffer
deallocation is not part of bufferization per se.
Differential Revision: https://reviews.llvm.org/D94351
TosaToLinalg was depending on its header file indirectly through
Passes.h rather than directly. This removes that indirection.
Differential Revision: https://reviews.llvm.org/D94706
This revision adds a new `replaceOpWithIf` hook that replaces uses of an operation that satisfy a given functor. If all uses are replaced, the operation gets erased in a similar manner to `replaceOp`. DialectConversion support will be added in a followup as this requires adjusting how replacements are tracked there.
Differential Revision: https://reviews.llvm.org/D94632
In the overwhelmingly common case, enum attribute case strings represent valid identifiers in MLIR syntax. This revision updates the format generator to format as a keyword in these cases, removing the need to wrap values in a string. The parser still retains the ability to parse the string form, but the printer will use the keyword form when applicable.
Differential Revision: https://reviews.llvm.org/D94575
This is a variant of TypesMatchWith that provides support for variadic arguments. This is necessary because ranges generally can't use the default operator== comparators for checking equality.
Differential Revision: https://reviews.llvm.org/D94574
Initial commit to add support for lowering from TOSA to Linalg. The focus is on
the essential infrastructure for these lowerings and integration with existing
passes.
Includes lowerings for a subset of operations including:
abs, add, sub, pow, and, or, xor, left shift, right shift, tanh
Lit tests are used to validate correctness.
Differential Revision: https://reviews.llvm.org/D94247
With this, we have complete support for emptiness checks. This also paves the way for future support to check if two FlatAffineConstraints are equal.
Reviewed By: ftynse
Differential Revision: https://reviews.llvm.org/D94272
Similar to the parallelization strategies, the vectorization strategies
provide control on what loops should be vectorize. Unlike the parallel
strategies, only innermost loops are considered, but including reductions,
with the control of vectorizing dense loops only or dense and sparse loops.
The vectorized loops are always controlled by a vector mask to avoid
overrunning the iterations, but subsequent vector operation folding removes
redundant masks and replaces the operations with more efficient counterparts.
Similarly, we will rely on subsequent loop optimizations to further optimize
masking, e.g. using an unconditional full vector loop and scalar cleanup loop.
The current strategy already demonstrates a nice interaction between the
sparse compiler and all prior optimizations that went into the vector dialect.
Ongoing discussion at:
https://llvm.discourse.group/t/mlir-support-for-sparse-tensors/2020/10
Reviewed By: penpornk
Differential Revision: https://reviews.llvm.org/D94551
This corrects the last 2 issues caught by tests when causing dialect
conversion rollbacks to occur.
Differential Revision: https://reviews.llvm.org/D94623
This commit adds support for parsing attribute uses in indexing
maps. These attribute uses are represented as affine symbols in
the resultant indexing maps because we can only know their
concrete value (which are coming from op attributes and are
constants) for specific op instances. The `indxing_maps()`
calls are synthesized to read these attributes and create affine
constants to replace the placeholder affine symbols and simplify.
Depends on D94240
Reviewed By: nicolasvasilache
Differential Revision: https://reviews.llvm.org/D94335
An invalid permutation will trigger a C++ assertion when attempting to create an AffineMap from the permutation.
This patch adds an `isPermutation` function to check the given permutation before creating the AffineMap.
Reviewed By: mehdi_amini
Differential Revision: https://reviews.llvm.org/D94492
This avoids large source files and gives a better structure. It also
allows leveraging compilation parallelism.
Reviewed By: mravishankar
Differential Revision: https://reviews.llvm.org/D94360
With this, now we can specify a list of attributes on named ops
generated from the spec. The format is defined as
```
attr-id ::= bare-id (`?`)?
attr-typedef ::= type (`[` `]`)?
attr-def ::= attr-id `:` attr-typedef
tc-attr-def ::= `attr` `(` attr-def-list `)`
tc-def ::= `def` bare-id
`(`tensor-def-list`)` `->` `(` tensor-def-list`)`
(tc-attr-def)?
```
For example,
```
ods_def<SomeCppOp>
def some_op(...) -> (...)
attr(
f32_attr: f32,
i32_attr: i32,
array_attr : f32[],
optional_attr? : f32
)
```
where `?` means optional attribute and `[]` means array type.
Reviewed By: hanchung, nicolasvasilache
Differential Revision: https://reviews.llvm.org/D94240
This commit moves dangling ops in the main ops.td file to the proper
file matching their categories. This makes ops.td as purely including
all category files.
Differential Revision: https://reviews.llvm.org/D94413
Use TableGen and information in ACC.td for the Default enum in the OpenACC dialect.
This patch generalize what was done for OpenMP for directives.
Follow up patch after D93576
Reviewed By: kiranchandramohan
Differential Revision: https://reviews.llvm.org/D93710
This revision uniformizes fusion APIs to allow passing OpOperand, OpResult and adds a finer level of control fusion.
Differential Revision: https://reviews.llvm.org/D94493
Continue the convergence between LLVM dialect and built-in types by using the
built-in vector type whenever possible, that is for fixed vectors of built-in
integers and built-in floats. LLVM dialect vector type is still in use for
pointers, less frequent floating point types that do not have a built-in
equivalent, and scalable vectors. However, the top-level `LLVMVectorType` class
has been removed in favor of free functions capable of inspecting both built-in
and LLVM dialect vector types: `LLVM::getVectorElementType`,
`LLVM::getNumVectorElements` and `LLVM::getFixedVectorType`. Additional work is
necessary to design an implemented the extensions to built-in types so as to
remove the `LLVMFixedVectorType` entirely.
Note that the default output format for the built-in vectors does not have
whitespace around the `x` separator, e.g., `vector<4xf32>` as opposed to the
LLVM dialect vector type format that does, e.g., `!llvm.vec<4 x fp128>`. This
required changing the FileCheck patterns in several tests.
Reviewed By: mehdi_amini, silvas
Differential Revision: https://reviews.llvm.org/D94405
getDynOperands behavior is commonly used in a number of passes. Refactored to
use a helper function and avoid code reuse.
Differential Revision: https://reviews.llvm.org/D94340
Based on the comments in lib/Parser/TypeParser.cpp on the
parseMemRefType and parseTensorType functions.
Reviewed By: mehdi_amini
Differential Revision: https://reviews.llvm.org/D94262
This ensures the memref base + indices expression is well-formed
Reviewed By: ThomasRaoux, ftynse
Differential Revision: https://reviews.llvm.org/D94441
This reverts commit df86f15f0c53c395dac5a14aba08745bc12b9b9b.
The gcc-5 build was broken by this change:
mlir/tools/mlir-linalg-ods-gen/mlir-linalg-ods-gen.cpp:1275:77: required from here
/usr/include/c++/5/ext/new_allocator.h:120:4: error: no matching function for call to 'std::pair<const std::__cxx11::basic_string<char>, {anonymous}::TCParser::RegisteredAttr>::pair(llvm::StringRef&, {anonymous}::TCParser::RegisteredAttr'
* Registers a small set of sample dialects.
* NFC with respect to existing C-API symbols but some headers have been moved down a level to the Dialect/ sub-directory.
* Adds an additional entry point per dialect that is needed for dynamic discovery/loading.
* See discussion: https://llvm.discourse.group/t/dialects-and-the-c-api/2306/16
Differential Revision: https://reviews.llvm.org/D94370
* We've got significant missing features in order to use most of these effectively (i.e. custom builders, region-based builders).
* We presently also lack a mechanism for actually registering these dialects but they can be use with contexts that allow unregistered dialects for further prototyping.
Differential Revision: https://reviews.llvm.org/D94368
The type tablegen backend now has enough support to represent these types well enough, so we can now move them to be declaratively defined.
Differential Revision: https://reviews.llvm.org/D94275
