The SSA values created with `shape.const_size` are now named depending on the
value.
A constant size of 3, e.g., is now automatically named `%c3`.
Differential Revision: https://reviews.llvm.org/D81249
The operations `to_extent_tensor` and `from_extent_tensor` become no-ops when
lowered to the standard dialect.
This is possible with a lowering from `shape.shape` to `tensor<?xindex>`.
Differential Revision: https://reviews.llvm.org/D81162
This parameter gives the developers the freedom to choose their desired function
signature conversion for preparing their functions for buffer placement. It is
introduced for BufferAssignmentFuncOpConverter, and also for
BufferAssignmentReturnOpConverter, and BufferAssignmentCallOpConverter to adapt
the return and call operations with the selected function signature conversion.
If the parameter is set, buffer placement won't also deallocate the returned
buffers.
Differential Revision: https://reviews.llvm.org/D81137
This patch is a follow-up on https://reviews.llvm.org/D81127
BF16 constants were represented as 64-bit floating point values due to the lack
of support for BF16 in APFloat. APFloat was recently extended to support
BF16 so this patch is fixing the BF16 constant representation to be 16-bit.
Reviewed By: rriddle
Differential Revision: https://reviews.llvm.org/D81218
Summary:
This revision adds a common folding pattern that starts appearing on
vector_transfer ops.
Differential Revision: https://reviews.llvm.org/D81281
Summary:
`mlir-rocm-runner` is introduced in this commit to execute GPU modules on ROCm
platform. A small wrapper to encapsulate ROCm's HIP runtime API is also inside
the commit.
Due to behavior of ROCm, raw pointers inside memrefs passed to `gpu.launch`
must be modified on the host side to properly capture the pointer values
addressable on the GPU.
LLVM MC is used to assemble AMD GCN ISA coming out from
`ConvertGPUKernelToBlobPass` to binary form, and LLD is used to produce a shared
ELF object which could be loaded by ROCm HIP runtime.
gfx900 is the default target be used right now, although it could be altered via
an option in `mlir-rocm-runner`. Future revisions may consider using ROCm Agent
Enumerator to detect the right target on the system.
Notice AMDGPU Code Object V2 is used in this revision. Future enhancements may
upgrade to AMDGPU Code Object V3.
Bitcode libraries in ROCm-Device-Libs, which implements math routines exposed in
`rocdl` dialect are not yet linked, and is left as a TODO in the logic.
Reviewers: herhut
Subscribers: mgorny, tpr, dexonsmith, mehdi_amini, rriddle, jpienaar, shauheen, antiagainst, nicolasvasilache, csigg, arpith-jacob, mgester, lucyrfox, aartbik, liufengdb, stephenneuendorffer, Joonsoo, grosul1, frgossen, Kayjukh, jurahul, llvm-commits
Tags: #mlir, #llvm
Differential Revision: https://reviews.llvm.org/D80676
Add support for flat, location, and noperspective decorations in the
serializer and deserializer to be able to process basic shader files
for graphics applications.
Differential Revision: https://reviews.llvm.org/D80837
Recently introduced allocation hoisting is quite conservative on the cases when it triggers.
This revision makes it such that the allocations for vector transfer lowerings are hoisted
to the top of the function.
This should be revisited in the context of parallelism and is a temporary workaround.
Differential Revision: https://reviews.llvm.org/D81253
This revision adds a helper function to hoist vector.transfer_read /
vector.transfer_write pairs out of immediately enclosing scf::ForOp
iteratively, if the following conditions are true:
1. The 2 ops access the same memref with the same indices.
2. All operands are invariant under the enclosing scf::ForOp.
3. No uses of the memref either dominate the transfer_read or are
dominated by the transfer_write (i.e. no aliasing between the write and
the read across the loop)
To improve hoisting opportunities, call the `moveLoopInvariantCode` helper
function on the candidate loop above which to hoist. Hoisting the transfers
results in scf::ForOp yielding the value that originally transited through
memory.
This revision additionally exposes `moveLoopInvariantCode` as a helper in
LoopUtils.h and updates SliceAnalysis to support return scf::For values and
allow hoisting across multiple scf::ForOps.
Differential Revision: https://reviews.llvm.org/D81199
Summary:
This will inline the region to a shape.assuming in the case that the
input witness is found to be statically true.
Differential Revision: https://reviews.llvm.org/D80302
In the case of all inputs being constant and equal, cstr_eq will be
replaced with a true_witness.
Differential Revision: https://reviews.llvm.org/D80303
This allows replacing of this op with a true witness in the case of both
inputs being const_shapes and being found to be broadcastable.
Differential Revision: https://reviews.llvm.org/D80304
This allows assuming_all to be replaced when all inputs are known to be
statically passing witnesses.
Differential Revision: https://reviews.llvm.org/D80306
This will later be used during canonicalization and folding steps to replace
statically known passing constraints.
Differential Revision: https://reviews.llvm.org/D80307
Update linalg to affine lowering for convop to use affine load for input
whenever there is no padding. It had always been using std.loads because
max in index functions (needed for non-zero padding if not materializing
zeros) couldn't be represented in the non-zero padding cases.
In the future, the non-zero padding case could also be made to use
affine - either by materializing or using affine.execute_region. The
latter approach will not impact the scf/std output obtained after
lowering out affine.
Differential Revision: https://reviews.llvm.org/D81191
This simplifies a lot of handling of BoolAttr/IntegerAttr. For example, a lot of places currently have to handle both IntegerAttr and BoolAttr. In other places, a decision is made to pick one which can lead to surprising results for users. For example, DenseElementsAttr currently uses BoolAttr for i1 even if the user initialized it with an Array of i1 IntegerAttrs.
Differential Revision: https://reviews.llvm.org/D81047
This revision adds a helper function to hoist alloc/dealloc pairs and
alloca op out of immediately enclosing scf::ForOp if both conditions are true:
1. all operands are defined outside the loop.
2. all uses are ViewLikeOp or DeallocOp.
This is now considered Linalg-specific and will be generalized on a per-need basis.
Differential Revision: https://reviews.llvm.org/D81152
Add SubgroupId, SubgroupSize and NumSubgroups to GPU dialect ops and add the
lowering of those ops to SPIRV.
Differential Revision: https://reviews.llvm.org/D81042
Summary:
The fusion for tensor_reshape is embedding the information to indexing maps,
thus the exising pattenr also works for indexed_generic ops.
Depends On D80347
Differential Revision: https://reviews.llvm.org/D80348
Summary:
Different from the fusion between generic ops, indices are involved. In this
context, we need to re-map the indices for producer since the fused op is built
on consumer's perspective. This patch supports all combination of the fusion
between indexed_generic ops and generic ops, which includes tests case:
1) generic op as producer and indexed_generic op as consumer.
2) indexed_generic op as producer and generic op as consumer.
3) indexed_generic op as producer and indexed_generic op as consumer.
Differential Revision: https://reviews.llvm.org/D80347
Summary:
Progressive lowering of vector.transpose into an operation that
is closer to an intrinsic, and thus the hardware ISA. Currently
under the common vector transform testing flag, as we prepare
deploying this transformation in the LLVM lowering pipeline.
Reviewers: nicolasvasilache, reidtatge, andydavis1, ftynse
Reviewed By: nicolasvasilache, ftynse
Subscribers: mehdi_amini, rriddle, jpienaar, shauheen, antiagainst, nicolasvasilache, arpith-jacob, mgester, lucyrfox, liufengdb, stephenneuendorffer, Joonsoo, grosul1, frgossen, Kayjukh, jurahul, llvm-commits
Tags: #llvm, #mlir
Differential Revision: https://reviews.llvm.org/D80772
Add a new pass to lower operations from the `shape` to the `std` dialect.
The conversion applies only to the `size_to_index` and `index_to_size`
operations and affected types.
Other patterns will be added as needed.
Differential Revision: https://reviews.llvm.org/D81091
Alexander Belyaev