This aligns the SCF dialect file layout with the majority of the dialects.
Reviewed By: jpienaar
Differential Revision: https://reviews.llvm.org/D128049
This change adds a transformation and pass to the NvGPU dialect that
attempts to optimize reads/writes from a memref representing GPU shared
memory in order to avoid bank conflicts. Given a value representing a
shared memory memref, it traverses all reads/writes within the parent op
and, subject to suitable conditions, rewrites all last dimension index
values such that element locations in the final (col) dimension are
given by
`newColIdx = col % vecSize + perm[row](col/vecSize,row)`
where `perm` is a permutation function indexed by `row` and `vecSize`
is the vector access size in elements (currently assumes 128bit
vectorized accesses, but this can be made a parameter). This specific
transformation can help optimize typical distributed & vectorized accesses
common to loading matrix multiplication operands to/from shared memory.
Differential Revision: https://reviews.llvm.org/D127457
This changes adds the option to lower to NvGpu dialect ops during the
VectorToGPU convsersion pass. Because this transformation reuses
existing VectorToGPU logic, a seperate VectorToNvGpu conversion pass is
not created. The option `use-nvgpu` is added to the VectorToGPU pass.
When this is true, the pass will attempt to convert slices rooted at
`vector.contract` operations into `nvgpu.mma.sync` ops, and
`vector.transfer_read` ops are converted to either `nvgpu.ldmatrix` or
one or more `vector.load` operations. The specific data loaded will
depend on the thread id within a subgroup (warp). These index
calculations depend on data type and shape of the MMA op
according to the downstream PTX specification. The code for supporting
these details is separated into `NvGpuSupport.cpp|h`.
Differential Revision: https://reviews.llvm.org/D122940
This has been on _Both for a couple of weeks. Flip usages in core with
intention to flip flag to _Prefixed in follow up. Needed to add a couple
of helper methods in AffineOps and Linalg to facilitate a pure flag flip
in follow up as some of these classes are used in templates and so
sensitive to Vector dialect changes.
Differential Revision: https://reviews.llvm.org/D122151
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
This reduces the dependencies of the MLIRVector target and makes the dialect consistent with other dialects.
Differential Revision: https://reviews.llvm.org/D118533
BlockArguments gained the ability to have locations attached a while ago, but they
have always been optional. This goes against the core tenant of MLIR where location
information is a requirement, so this commit updates the API to require locations.
Fixes#53279
Differential Revision: https://reviews.llvm.org/D117633
The only benefit of FunctionPass is that it filters out function
declarations. This isn't enough to justify carrying it around, as we can
simplify filter out declarations when necessary within the pass. We can
also explore with better scheduling primitives to filter out declarations
at the pipeline level in the future.
The definition of FunctionPass is left intact for now to allow time for downstream
users to migrate.
Differential Revision: https://reviews.llvm.org/D117182
This revision adds 0-d vector support to vector.transfer ops.
In the process, numerous cleanups are applied, in particular around normalizing
and reducing the number of builders.
Reviewed By: ThomasRaoux, springerm
Differential Revision: https://reviews.llvm.org/D114803
Support load with broadcast, elementwise divf op and remove the
hardcoded restriction on the vector size. Picking the right size should
be enfored by user and will fail conversion to llvm/spirv if it is not
supported.
Differential Revision: https://reviews.llvm.org/D113618
This predates the templated variant, and has been simply forwarding
to getSplatValue<Attribute> for some time. Removing this makes the
API a bit more uniform, and also helps prevent users from thinking
it is "cheap".
Precursor: https://reviews.llvm.org/D110200
Removed redundant ops from the standard dialect that were moved to the
`arith` or `math` dialects.
Renamed all instances of operations in the codebase and in tests.
Reviewed By: rriddle, jpienaar
Differential Revision: https://reviews.llvm.org/D110797
* Remove dependency: Standard --> MemRef
* Add dependencies: GPUToNVVMTransforms --> MemRef, Linalg --> MemRef, MemRef --> Tensor
* Note: The `subtensor_insert_propagate_dest_cast` test case in MemRef/canonicalize.mlir will be moved to Tensor/canonicalize.mlir in a subsequent commit, which moves over the remaining Tensor ops from the Standard dialect to the Tensor dialect.
Differential Revision: https://reviews.llvm.org/D104506
This is the first step to convert vector ops to MMA operations in order to
target GPUs tensor core ops. This currently only support simple cases,
transpose and element-wise operation will be added later.
Differential Revision: https://reviews.llvm.org/D102962
