This still satisfies the constraints required by the affine dialect and
gives more flexibility in what iteration bounds can be used when
loewring to the GPU dialect.
Differential Revision: https://reviews.llvm.org/D89782
The Value hierarchy consists of BlockArgument and OpResult, both of which
derive Value. Introduce IsA functions and functions specific to each class,
similarly to other class hierarchies. Also, introduce functions for
pointer-comparison of Block and Operation that are necessary for testing and
are generally useful.
Reviewed By: stellaraccident, mehdi_amini
Differential Revision: https://reviews.llvm.org/D89714
* Interops with Python buffers/numpy arrays to create.
* Also cleans up 'get' factory methods on some types to be consistent.
* Adds mlirAttributeGetType() to C-API to facilitate error handling and other uses.
* Punts on a lot of features of the ElementsAttribute hierarchy for now.
* Does not yet support bool or string attributes.
Reviewed By: ftynse
Differential Revision: https://reviews.llvm.org/D89363
Now, convert-shape-to-std doesn't internally create memrefs, which was
previously a bit of a layering violation. The conversion to memrefs
should logically happen as part of bufferization.
Differential Revision: https://reviews.llvm.org/D89669
It's unfortunate that this requires adding a dependency on scf dialect
to std bufferization (and hence all of std transforms). This is a bit
perilous. We might want a lib/Transforms/Bufferize/ with a separate
bufferization library per dialect?
Differential Revision: https://reviews.llvm.org/D89667
Move the class to where all base classes are defined.
Also remove all the builders since they are definted in subclasses anyway.
Differential Revision: https://reviews.llvm.org/D89620
The current BufferPlacement transformation contains several concepts for
hoisting allocations. However, more advanced hoisting techniques should not be
integrated into the BufferPlacement transformation. Hence, this CL refactors the
current BufferPlacement pass into three separate pieces: BufferDeallocation and
BufferAllocation(Loop)Hoisting. Moreover, it extends the hoisting functionality
by allowing to move allocations out of loops.
Differential Revision: https://reviews.llvm.org/D87756
LLVM dialect has been defining Op arguments by deriving the `Arguments` ODS
class. This has arguably worse readability due to large indentation caused by
multiple derivations, and is inconsistent with other ODS files. Use the `let
arguments` form instead.
Reviewed By: rriddle
Differential Revision: https://reviews.llvm.org/D89560
Usage of nested parallel regions were not working correctly and leading
to assertion failures. Fix contains the following changes,
1) Don't set the insertion point in the body callback.
2) Save the continuation IP in a stack and set the branch to
continuationIP at the terminator.
Reviewed By: SouraVX, jdoerfert, ftynse
Differential Revision: https://reviews.llvm.org/D88720
AllReduceLowering is currently the only GPU rewrite pattern, but more are coming. This is a preparation change.
Reviewed By: herhut
Differential Revision: https://reviews.llvm.org/D89370
Have the ODS TypeDef generator write the getChecked() definition.
Also add to TypeParamCommaFormatter a `JustParams` format and
refactor around that.
Reviewed By: rriddle
Differential Revision: https://reviews.llvm.org/D89438
This transforms the symbol lookups to O(1) from O(NM), greatly speeding up both passes. For a large MLIR module this shaved seconds off of the compilation time.
Differential Revision: https://reviews.llvm.org/D89522
The initial goal of this interface is to fix the current problems with verifying symbol user operations, but can extend beyond that in the future. The current problems with the verification of symbol uses are:
* Extremely inefficient:
Most current symbol users perform the symbol lookup using the slow O(N) string compare methods, which can lead to extremely long verification times in large modules.
* Invalid/break the constraints of verification pass
If the symbol reference is not-flat(and even if it is flat in some cases) a verifier for an operation is not permitted to touch the referenced operation because it may be in the process of being mutated by a different thread within the pass manager.
The new SymbolUserOpInterface exposes a method `verifySymbolUses` that will be invoked from the parent symbol table to allow for verifying the constraints of any referenced symbols. This method is passed a `SymbolTableCollection` to allow for O(1) lookups of any necessary symbol operation.
Differential Revision: https://reviews.llvm.org/D89512
This revision contains two optimizations related to symbol checking:
* Optimize SymbolOpInterface to only check for a name attribute if the operation is an optional symbol.
This removes an otherwise unnecessary attribute lookup from a majority of symbols.
* Add a new SymbolTableCollection class to represent a collection of SymbolTables.
This allows for perfoming non-flat symbol lookups in O(1) time by caching SymbolTables for symbol table operations. This class is very useful for algorithms that operate on multiple symbol tables, either recursively or not.
Differential Revision: https://reviews.llvm.org/D89505
(Note: This is a reland of D82597)
This class allows for defining thread local objects that have a set non-static lifetime. This internals of the cache use a static thread_local map between the various different non-static objects and the desired value type. When a non-static object destructs, it simply nulls out the entry in the static map. This will leave an entry in the map, but erase any of the data for the associated value. The current use cases for this are in the MLIRContext, meaning that the number of items in the static map is ~1-2 which aren't particularly costly enough to warrant the complexity of pruning. If a use case arises that requires pruning of the map, the functionality can be added.
This is especially useful in the context of MLIR for implementing thread-local caching of context level objects that would otherwise have very high lock contention. This revision adds a thread local cache in the MLIRContext for attributes, identifiers, and types to reduce some of the locking burden. This led to a speedup of several seconds when compiling a somewhat large mlir module.
Differential Revision: https://reviews.llvm.org/D89504
This trait simply adds a fold of f(f(x)) = f(x) when an operation is labelled as idempotent
Reviewed By: rriddle, andyly
Differential Revision: https://reviews.llvm.org/D89421
* Also fixes the const-ness of the various DenseElementsAttr construction functions.
* Both issues identified when trying to use the DenseElementsAttr functions.
Differential Revision: https://reviews.llvm.org/D89517
Added an underlying matcher for generic constant ops. This
included a rewriter of RewriterGen to make variable use more
clear.
Differential Revision: https://reviews.llvm.org/D89161
Adding unroll support for transfer read and transfer write operation. This
allows to pick the ideal size for the memory access for a given target.
Differential Revision: https://reviews.llvm.org/D89289
The opposite of tensor_to_memref is tensor_load.
- Add some basic tensor_load/tensor_to_memref folding.
- Add source/target materializations to BufferizeTypeConverter.
- Add an example std bufferization pattern/pass that shows how the
materialiations work together (more std bufferization patterns to come
in subsequent commits).
- In coming commits, I'll document how to write composable
bufferization passes/patterns and update the other in-tree
bufferization passes to match this convention. The populate* functions
will of course continue to be exposed for power users.
The naming on tensor_load/tensor_to_memref and their pretty forms are
not very intuitive. I'm open to any suggestions here. One key
observation is that the memref type must always be the one specified in
the pretty form, since the tensor type can be inferred from the memref
type but not vice-versa.
With this, I've been able to replace all my custom bufferization type
converters in npcomp with BufferizeTypeConverter!
Part of the plan discussed in:
https://llvm.discourse.group/t/what-is-the-strategy-for-tensor-memref-conversion-bufferization/1938/17
Differential Revision: https://reviews.llvm.org/D89437
Parsing of a scalar subview did not create the required static_offsets attribute.
This also adds support for folding scalar subviews away.
Differential Revision: https://reviews.llvm.org/D89467
Each hardware that supports SPV_C_CooperativeMatrixNV has a list of
configurations that are supported natively. Add an attribute to
specify the configurations supported to the `spv.target_env`.
Reviewed By: antiagainst, ThomasRaoux
Differential Revision: https://reviews.llvm.org/D89364
The current fusion on tensors fuses reshape ops with generic ops by
linearizing the indexing maps of the fused tensor in the generic
op. This has some limitations
- It only works for static shapes
- The resulting indexing map has a linearization that would be
potentially prevent fusion later on (for ex. tile + fuse).
Instead, try to fuse the reshape consumer (producer) with generic op
producer (consumer) by expanding the dimensionality of the generic op
when the reshape is expanding (folding). This approach conflicts with
the linearization approach. The expansion method is used instead of
the linearization method.
Further refactoring that changes the fusion on tensors to be a
collection of patterns.
Differential Revision: https://reviews.llvm.org/D89002
This CL allows user to specify the same name for the operands in the source pattern which implicitly enforces equality on operands with the same name.
E.g., Pat<(OpA $a, $b, $a) ... > would create a matching rule for checking equality for the first and the last operands. Equality of the operands is enforced at any depth, e.g., OpA ($a, $b, OpB($a, $c, OpC ($a))).
Example usage: Pat<(Reshape $arg0, (Shape $arg0)), (replaceWithValue $arg0)>
Note, this feature only covers operands but not attributes.
Current use cases are based on the operand equality and explicitly add the constraint into the pattern. Attribute equality will be worked out on the different CL.
Reviewed By: jpienaar
Differential Revision: https://reviews.llvm.org/D89254
The buffers are used as source or destination of transfer commands
so always add VK_BUFFER_USAGE_TRANSFER_{DST,SRC}_BIT to their usage
flags.
Signed-off-by: Kevin Petit <kevin.petit@arm.com>
This patch adds a couple missing LLVM IR dialect floating point types to
the legality check.
Reviewed By: ftynse
Differential Revision: https://reviews.llvm.org/D89350
This revision adds a programmable codegen strategy from linalg based on staged rewrite patterns. Testing is exercised on a simple linalg.matmul op.
Differential Revision: https://reviews.llvm.org/D89374
* It reads as more of a TODO for the future and has been long obsoleted by later work.
* One of the authors of the referenced paper called this out as "weird stuff from two years ago" when reviewing the more recent TOSA RFC.
Differential Revision: https://reviews.llvm.org/D89329
This reverts commit 7271c1bcb9.
This broke the gcc-5 build:
/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>, mlir::tblgen::SymbolInfoMap::SymbolInfo>::pair(llvm::StringRef&, mlir::tblgen::SymbolInfoMap::SymbolInfo)'
{ ::new((void *)__p) _Up(std::forward<_Args>(__args)...); }
^
In file included from /usr/include/c++/5/utility:70:0,
from llvm/include/llvm/Support/type_traits.h:18,
from llvm/include/llvm/Support/Casting.h:18,
from mlir/include/mlir/Support/LLVM.h:24,
from mlir/include/mlir/TableGen/Pattern.h:17,
from mlir/lib/TableGen/Pattern.cpp:14:
/usr/include/c++/5/bits/stl_pair.h:206:9: note: candidate: template<class ... _Args1, long unsigned int ..._Indexes1, class ... _Args2, long unsigned int ..._Indexes2> std::pair<_T1, _T2>::pair(std::tuple<_Args1 ...>&, std::tuple<_Args2 ...>&, std::_Index_tuple<_Indexes1 ...>, std::_Index_tuple<_Indexes2 ...>)
pair(tuple<_Args1...>&, tuple<_Args2...>&,
^
Tres Popp