Commit Graph

312 Commits

Author SHA1 Message Date
Aart Bik
7c1fb94150 [mlir][sparse] change runners to c_runners
Reviewed By: Peiming

Differential Revision: https://reviews.llvm.org/D150628
2023-05-15 18:17:52 -07:00
Aart Bik
c820f9e6ae [mlir][sparse][gpu] end-to-end integration test of GPU libgen approach
Reviewed By: Peiming

Differential Revision: https://reviews.llvm.org/D150172
2023-05-15 10:57:14 -07:00
Andrzej Warzynski
20bf8c403c [mlir][SparseTensor][ArmSVE] Disable scalable vectorisation in a test
The MLIR SVE integration tests are now enabled in the
clang-aarch64-full-2stage buildbot under emulation (QEMU) and one of the
sparse integration tests is failing [1]:

  * Integration/Dialect/SparseTensor/CPU/concatenate_dim_1.mlir

That test is failing because we we don't have a LIT substitution to
replace:
  ```
  ; RUN: mlir-cpu-runner <command>
  ```
with
  ```
  ; RUN: <emulator> mlir-cpu-runner <command>
  ```
clang-aarch64-full-2stage does not support SVE natively and hence all
SVE integration tests require emulation. Other SVE tests use `lli` (for
which we do have the required substitution) and hence are not affected.

This patch simplifies concatenate_dim_1.mlir to always use fixed-width
vectorisation. We will re-enable scalable vectorisation once LIT
substitutions for `mlir-cpu-runner` are updated.

[1] https://lab.llvm.org/buildbot/#/builders/179/builds/6062
2023-05-02 21:14:38 +00:00
Cullen Rhodes
707b6e94b8 [mlir][SparseTensor][ArmSVE] Fix missing lli substitutions
The MLIR SVE integration tests are now enabled in the
clang-aarch64-full-2stage buildbot under emulation (QEMU) and two of the
sparse integration tests are failing [1]:

  * mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_sorted_coo.mlir
  * mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_spmm.mlir

The reason for this is the SVE RUN lines use plain 'lli' rather than the
'%lli_host_or_aarch64_cmd' substitution that's necessary to run under
emulation. The CI doesn't support SVE so the tests will SIGILL unless
run under emulation.

I should note the logs don't show a SIGILL, only the non-descript:

  FileCheck error: '<stdin>' is empty.

but I expect this is what's actually happening.

https://lab.llvm.org/buildbot/#/builders/179/builds/6051/steps/12/logs/stdio
2023-05-02 14:43:48 +00:00
Peiming Liu
d4db528938 [mlir][sparse] extend unpack operation to support unpacking a batched COO type
Reviewed By: aartbik

Differential Revision: https://reviews.llvm.org/D149103
2023-05-01 18:17:29 +00:00
Cullen Rhodes
baafc74ab0 [mlir][test][Integration] Refactor Arm emulator configuration
The logic enabling the Arm SVE (and now SME) integration tests for
various dialects, that may run under emulation, is now duplicated in
several places.

This patch moves the configuration to the top-level MLIR integration
tests Lit config and renames the '%lli' substitution in contexts where
it will run exclusively (ArmSVE, ArmSME) on AArch64 (and possibly under
emulation) to '%lli_aarch64_cmd', and '%lli_host_or_aarch64_cmd' for
contexts where it may run AArch64 (also possibly under emulation). The
latter is for integration tests that have target-specific and
target-agnostic codepaths such as SparseTensor, which supports scalable
vectors.

The two substitutions have the same effect but the names are different to
convey this information. The '%lli_aarch64_cmd' substitution could be
used in the SparseTensor tests but that would be a misnomer if the host
were x86 and the MLIR_RUN_SVE_TESTS=OFF.

The reason for renaming the '%lli' substitution is to not prevent running other
target-specific integration tests at the same time, since the same substitution
'%lli' is used for lli in other integration tests:

  * mlir/test/Integration/Dialect/Vector/CPU/X86Vector              - (AVX emulation via Intel SDE)
  * mlir/test/Integration/Dialect/Vector/CPU/AMX                    - (AMX emulation via Intel SDE)
  * mlir/test/Integration/Dialect/LLVMIR/CPU/test-vp-intrinsic.mlir - (RISCV emulation via QEMU if supported, native otherwise)

and substituting '%lli' at the top-level with Arm specific logic would override
this.

Reviewed By: awarzynski

Differential Revision: https://reviews.llvm.org/D148929
2023-04-26 09:57:43 +00:00
Cullen Rhodes
c8d1388e6c [mlir][ArmSME] Add tests for Streaming SVE
This patch adds a couple of tests for targeting Arm Streaming SVE (SSVE)
mode, part of the Arm Scalable Matrix Extension (SME).

SSVE is enabled in the backend at the function boundary by specifying
the `aarch64_pstate_sm_enabled` attribute, as documented here [1]. SSVE
can be targeted from MLIR by specifying this in the passthrough
attributes [2] and compiling with

  -mattr=+sme,+sve -force-streaming-compatible-sve

The passthrough will propagate to the backend where `smstart/smstop`
will be emitted around the call to the SSVE function.

The set of legal instructions changes in SSVE,
`-force-streaming-compatible-sve` avoids the use of NEON entirely and
instead lowers to (streaming-compatible) SVE. The behaviour this flag
predicates will be hooked up to the function attribute in the future
such that simply specifying this (should) lead to correct
code-generation.

Two tests are added:

  * A basic LLVMIR test verifying the attribute is passed through.
  * An integration test calling a SSVE function.

The integration test can be run with QEMU.

[1] https://llvm.org/docs/AArch64SME.html
[2] https://mlir.llvm.org/docs/Dialects/LLVM/#attribute-pass-through

Reviewed By: awarzynski, aartbik

Differential Revision: https://reviews.llvm.org/D148111
2023-04-25 07:51:43 +00:00
Aart Bik
86888e420c [mlir][sparse][gpu] generate proper memcpy in/out host and device
The host registration is a convenient way to get CUDA kernels
running, but it may be slow and does not work for all buffer
(like global constants). This revision uses the proper alloc
copy dealloc chains for buffers, using asynchronous chains
to increase overlap. The host registration mechanism is
kept under a flag for the output, just for experimentation
purposes while this project ramps up.

Reviewed By: Peiming

Differential Revision: https://reviews.llvm.org/D148682
2023-04-21 09:30:42 -07:00
Peiming Liu
fd2211d84a use heap memory for position buffer allocated for PackOp.
Reviewed By: aartbik

Differential Revision: https://reviews.llvm.org/D148818
2023-04-20 20:26:01 +00:00
Peiming Liu
98f5a34097 [mlir][sparse] remove redundate integration tests.
The removed tests evaluate the same kernels in existing tests, namely `sparse_conv2d.mlir` and `spares_conv3d.mlir`.

Reviewed By: aartbik

Differential Revision: https://reviews.llvm.org/D148644
2023-04-18 18:30:43 +00:00
Peiming Liu
6a148c5aa7 [mlir][sparse] enable more sparse convolution kernels.
Reviewed By: aartbik

Differential Revision: https://reviews.llvm.org/D147670
2023-04-17 17:43:52 +00:00
Peiming Liu
2cd15925f4 [mlir][sparse] implement index redution on dense level (for CSR)
Reviewed By: aartbik

Differential Revision: https://reviews.llvm.org/D147550
2023-04-17 16:36:31 +00:00
Peiming Liu
5fd9d80135 [mlir][sparse] extend loop emitter to emit slice driven loops
Reviewed By: aartbik

Differential Revision: https://reviews.llvm.org/D142930
2023-04-13 03:29:40 +00:00
Aart Bik
bdea9b960d [mlir][sparse][gpu] put sparse compiler GPU end-to-end tests back
SM80 flag guards the test for targets that do not support A100 GPUs

Reviewed By: mehdi_amini

Differential Revision: https://reviews.llvm.org/D147863
2023-04-11 15:37:13 -07:00
Mehdi Amini
10dbf23edc Revert "[mlir][sparse][gpu] end-to-end example with sparse GPU pipeline"
This reverts commit bf94afa10e.

The bot is broken: https://lab.llvm.org/buildbot/#/builders/61/builds/42062
2023-04-06 19:11:27 -07:00
Mehdi Amini
103890fc07 Revert "[mlir][sparse][gpu] end-to-end test for 2:4 sparsity on NVidia GPUs"
This reverts commit a2c63d7f0b.

The bot is broken: https://lab.llvm.org/buildbot/#/builders/61/builds/42062
2023-04-06 19:11:27 -07:00
Aart Bik
bf94afa10e [mlir][sparse][gpu] end-to-end example with sparse GPU pipeline
Reviewed By: Peiming

Differential Revision: https://reviews.llvm.org/D147576
2023-04-05 16:10:21 -07:00
Andrzej Warzynski
c98372725b [mlir][sparse-compiler] Fix typo in a test
This patch fixes a type that was introduced in
https://reviews.llvm.org/D146917 and that triggered buildbot failure:
  * https://lab.llvm.org/buildbot#builders/220/builds/18225

This is rather straightforward (and fixes a bogus test failure), hence
sending without a review.
2023-03-31 07:49:18 +00:00
Andrzej Warzynski
fb0b035e35 [mlir-cpu-runner] Add support for -mattr and -march flags
This patch adds support for `-mattr` and `-march` in mlir-cpu-runner.
With this change, one should be able to consistently use mlir-cpu-runner
for MLIR's integration tests (instead of e.g. resorting to lli when some
additional flags are needed). This is demonstrated in
concatenate_dim_1.mlir.

In order to support the new flags, this patch makes sure that
MLIR's ExecutionEngine/JITRunner (that mlir-cpu-runner is built on top of):
  * takes into account the new command line flags when creating
    TargetMachine,
  * avoids recreating TargetMachine if one is already available,
  * creates LLVM's DataLayout based on the previously configured
    TargetMachine.
This is necessary in order to make sure that the command line
configuration is propagated correctly to the backend code generator.

A few additional updates are made in order to facilitate this change,
including support for debug dumps from JITRunner.

Differential Revision: https://reviews.llvm.org/D146917
2023-03-31 07:34:24 +00:00
Aart Bik
a2c63d7f0b [mlir][sparse][gpu] end-to-end test for 2:4 sparsity on NVidia GPUs
Example of using 2:4 sparsity on NVidia GPU

Reviewed By: ThomasRaoux

Differential Revision: https://reviews.llvm.org/D145447
2023-03-21 13:32:43 -07:00
Peiming Liu
f7ce987ec0 [mlir][sparse] add a coo slices matmul integration test.
Reviewed By: wrengr

Differential Revision: https://reviews.llvm.org/D146248
2023-03-16 20:03:26 +00:00
Peiming Liu
5da8f30d63 [mlir][sparse] add test cases for sparse tensor slices on COO tensors
Reviewed By: aartbik, bixia

Differential Revision: https://reviews.llvm.org/D146074
2023-03-16 16:43:56 +00:00
Peiming Liu
6db397a8d4 [mlir][sparse] support dynamic sparse tensor slices.
Reviewed By: aartbik

Differential Revision: https://reviews.llvm.org/D141532
2023-03-10 23:12:41 +00:00
Aart Bik
e1b3c5c403 [sparse][mlir] test transposition on sorted COO
DO NOT SUBMIT YET, test exposes bug

Reviewed By: Peiming

Differential Revision: https://reviews.llvm.org/D145708
2023-03-09 14:01:51 -08:00
Peiming Liu
4fa3cc6eb4 [mlir][sparse] deduplicate non-unique coordinates when coiterating collapsed COO tensors.
Reviewed By: aartbik

Differential Revision: https://reviews.llvm.org/D145532
2023-03-09 18:15:12 +00:00
Peiming Liu
cc009334eb [mlir][sparse] deduplicate non-unique coordinates when coiterating COO tensors
Reviewed By: aartbik

Differential Revision: https://reviews.llvm.org/D145518
2023-03-07 21:52:38 +00:00
wren romano
84cd51bb97 [mlir][sparse] Renaming "pointer/index" to "position/coordinate"
The old "pointer/index" names often cause confusion since these names clash with names of unrelated things in MLIR; so this change rectifies this by changing everything to use "position/coordinate" terminology instead.

In addition to the basic terminology, there have also been various conventions for making certain distinctions like: (1) the overall storage for coordinates in the sparse-tensor, vs the particular collection of coordinates of a given element; and (2) particular coordinates given as a `Value` or `TypedValue<MemRefType>`, vs particular coordinates given as `ValueRange` or similar.  I have striven to maintain these distinctions
as follows:

  * "p/c" are used for individual position/coordinate values, when there is no risk of confusion.  (Just like we use "d/l" to abbreviate "dim/lvl".)

  * "pos/crd" are used for individual position/coordinate values, when a longer name is helpful to avoid ambiguity or to form compound names (e.g., "parentPos").  (Just like we use "dim/lvl" when we need a longer form of "d/l".)

    I have also used these forms for a handful of compound names where the old name had been using a three-letter form previously, even though a longer form would be more appropriate.  I've avoided renaming these to use a longer form purely for expediency sake, since changing them would require a cascade of other renamings.  They should be updated to follow the new naming scheme, but that can be done in future patches.

  * "coords" is used for the complete collection of crd values associated with a single element.  In the runtime library this includes both `std::vector` and raw pointer representations.  In the compiler, this is used specifically for buffer variables with C++ type `Value`, `TypedValue<MemRefType>`, etc.

    The bare form "coords" is discouraged, since it fails to make the dim/lvl distinction; so the compound names "dimCoords/lvlCoords" should be used instead.  (Though there may exist a rare few cases where is is appropriate to be intentionally ambiguous about what coordinate-space the coords live in; in which case the bare "coords" is appropriate.)

    There is seldom the need for the pos variant of this notion.  In most circumstances we use the term "cursor", since the same buffer is reused for a 'moving' pos-collection.

  * "dcvs/lcvs" is used in the compiler as the `ValueRange` analogue of "dimCoords/lvlCoords".  (The "vs" stands for "`Value`s".)  I haven't found the need for it, but "pvs" would be the obvious name for a pos-`ValueRange`.

    The old "ind"-vs-"ivs" naming scheme does not seem to have been sustained in more recent code, which instead prefers other mnemonics (e.g., adding "Buf" to the end of the names for `TypeValue<MemRefType>`).  I have cleaned up a lot of these to follow the "coords"-vs-"cvs" naming scheme, though haven't done an exhaustive cleanup.

  * "positions/coordinates" are used for larger collections of pos/crd values; in particular, these are used when referring to the complete sparse-tensor storage components.

    I also prefer to use these unabbreviated names in the documentation, unless there is some specific reason why using the abbreviated forms helps resolve ambiguity.

In addition to making this terminology change, this change also does some cleanup along the way:
  * correcting the dim/lvl terminology in certain places.
  * adding `const` when it requires no other code changes.
  * miscellaneous cleanup that was entailed in order to make the proper distinctions.  Most of these are in CodegenUtils.{h,cpp}

Reviewed By: aartbik

Differential Revision: https://reviews.llvm.org/D144773
2023-03-06 12:23:33 -08:00
rkayaith
c00f81cc46 [mlir][python] Allow running pass manager on any operation
`PassManager.run` is currently restricted to running on `builtin.module`
ops, but this restriction doesn't exist on the C++ side. This updates it
to take `ir.Operation/OpView` instead of `ir.Module`.

Depends on D143354

Reviewed By: mehdi_amini

Differential Revision: https://reviews.llvm.org/D143356
2023-03-01 18:17:14 -05:00
Peiming Liu
b60cf8c972 [mlir][sparse] support coiteration with fused reshape tensor
Reviewed By: aartbik

Differential Revision: https://reviews.llvm.org/D145091
2023-03-01 20:55:46 +00:00
Peiming Liu
fc126022e8 [mlir][sparse] fuse collapse_shape on sparse tensor with GenericOp.
Instead of always materializing a new sparse tensor after reshape, this patch tries to fuses the reshape (currently only on COO) with GenericOp and coiterates with the reshaped tensors without allocating a new sparse tensor.

Reviewed By: aartbik

Differential Revision: https://reviews.llvm.org/D145016
2023-03-01 19:05:48 +00:00
bixia1
27ea470f22 [mlir][sparse] Add runtime support for reading a COO tensor and writing the data to the given indices and values buffers.
Reviewed By: aartbik

Differential Revision: https://reviews.llvm.org/D143862
2023-02-28 08:28:13 -08:00
Peiming Liu
85dbb3fc4b [mlir][sparse] support sparse tensor element type conversion in codegen path
Reviewed By: aartbik

Differential Revision: https://reviews.llvm.org/D144578
2023-02-23 17:49:50 +00:00
Peiming Liu
e6758c81f8 [mlir][sparse] comment out test cases in sparse_conversion with similiar behavior.
Reviewed By: aartbik

Differential Revision: https://reviews.llvm.org/D144236
2023-02-17 01:15:35 +00:00
Peiming Liu
0af5f84a13 [mlir][sparse] split reshape.mlir into expand/collapse_shape.mlir.
Reviewed By: aartbik

Differential Revision: https://reviews.llvm.org/D144231
2023-02-17 00:07:41 +00:00
Peiming Liu
9e8d9316ce [mlir][sparse] allow foreach operation to generate out-of-order loop on non-annotated tensor.
No need for a temp COO and sort even when converting dense -> CSC, we can instead rotate the loop to yield a ordered coordinates at beginning.

Reviewed By: aartbik

Differential Revision: https://reviews.llvm.org/D144213
2023-02-16 23:23:20 +00:00
bixia1
c2e248c6ae [mlir][sparse] Remove the expansion of symmetric MTX in the sparse tensor storage.
We will support symmetric MTX without expanding the data in the sparse tensor
storage.

Reviewed By: aartbik

Differential Revision: https://reviews.llvm.org/D144059
2023-02-16 13:02:17 -08:00
Peiming Liu
f30ca850ef [mlir][sparse] reduce the input size in stress_test.py to make it finish in time.
Reviewed By: aartbik

Differential Revision: https://reviews.llvm.org/D144150
2023-02-16 01:18:03 +00:00
Peiming Liu
e2e83f4c8f [mlir][sparse] support coiteration over sparse tensor slices
Reviewed By: aartbik

Differential Revision: https://reviews.llvm.org/D140736
2023-02-15 23:52:22 +00:00
Peiming Liu
7d62bc9cd3 [mlir][sparse] disable sparse convolution test cases.
These test cases will be re-enabled after new algorithm is implemented.

Reviewed By: aartbik

Differential Revision: https://reviews.llvm.org/D144141
2023-02-15 23:21:35 +00:00
Peiming Liu
9ed587ea9b [mlir][sparse] split sparse concatenate test cases smaller ones.
To allow a better parallelization.

Reviewed By: aartbik

Differential Revision: https://reviews.llvm.org/D144139
2023-02-15 22:54:18 +00:00
Markus Böck
9048ea28da Reland "[mlir] Make the vast majority of intgration and runner tests work on Windows"
This reverts commit 5561e17411

The logic was moved from cmake into lit fixing the issue that lead to the revert and potentially others with multi-config cmake generators

Differential Revision: https://reviews.llvm.org/D143925
2023-02-15 19:14:43 +01:00
Aart Bik
5561e17411 Revert "[mlir] Make the vast majority of integration and runner tests work on Windows"
This reverts commit 161b9d741a.

REASON:

cmake --build . --target check-mlir-integration

Failed Tests (186):
  MLIR :: Integration/Dialect/Arith/CPU/test-wide-int-emulation-addi-i16.mlir
  MLIR :: Integration/Dialect/Arith/CPU/test-wide-int-emulation-cmpi-i16.mlir
  MLIR :: Integration/Dialect/Arith/CPU/test-wide-int-emulation-compare-results-i16.mlir
  MLIR :: Integration/Dialect/Arith/CPU/test-wide-int-emulation-constants-i16.mlir
  MLIR :: Integration/Dialect/Arith/CPU/test-wide-int-emulation-max-min-i16.mlir
  MLIR :: Integration/Dialect/Arith/CPU/test-wide-int-emulation-muli-i16.mlir
  MLIR :: Integration/Dialect/Arith/CPU/test-wide-int-emulation-shli-i16.mlir
  MLIR :: Integration/Dialect/Arith/CPU/test-wide-int-emulation-shrsi-i16.mlir
  MLIR :: Integration/Dialect/Arith/CPU/test-wide-int-emulation-shrui-i16.mlir
  MLIR :: Integration/Dialect/Async/CPU/microbench-linalg-async-parallel-for.mlir
  MLIR :: Integration/Dialect/Async/CPU/microbench-scf-async-parallel-for.mlir
  MLIR :: Integration/Dialect/Async/CPU/test-async-parallel-for-1d.mlir
  MLIR :: Integration/Dialect/Async/CPU/test-async-parallel-for-2d.mlir
  MLIR :: Integration/Dialect/Complex/CPU/correctness.mlir
  MLIR :: Integration/Dialect/LLVMIR/CPU/X86/test-inline-asm-vector.mlir
  MLIR :: Integration/Dialect/LLVMIR/CPU/X86/test-inline-asm.mlir
  MLIR :: Integration/Dialect/LLVMIR/CPU/test-vector-reductions-fp.mlir
  MLIR :: Integration/Dialect/LLVMIR/CPU/test-vector-reductions-int.mlir
  MLIR :: Integration/Dialect/Linalg/CPU/matmul-vs-matvec.mlir
  MLIR :: Integration/Dialect/Linalg/CPU/rank-reducing-subview.mlir
  MLIR :: Integration/Dialect/Linalg/CPU/test-collapse-tensor.mlir
  MLIR :: Integration/Dialect/Linalg/CPU/test-conv-1d-call.mlir
  MLIR :: Integration/Dialect/Linalg/CPU/test-conv-1d-nwc-wcf-call.mlir
  MLIR :: Integration/Dialect/Linalg/CPU/test-conv-2d-call.mlir
  MLIR :: Integration/Dialect/Linalg/CPU/test-conv-2d-nhwc-hwcf-call.mlir
  MLIR :: Integration/Dialect/Linalg/CPU/test-conv-3d-call.mlir
  MLIR :: Integration/Dialect/Linalg/CPU/test-conv-3d-ndhwc-dhwcf-call.mlir
  MLIR :: Integration/Dialect/Linalg/CPU/test-elementwise.mlir
  MLIR :: Integration/Dialect/Linalg/CPU/test-expand-tensor.mlir
  MLIR :: Integration/Dialect/Linalg/CPU/test-one-shot-bufferize.mlir
  MLIR :: Integration/Dialect/Linalg/CPU/test-padtensor.mlir
  MLIR :: Integration/Dialect/Linalg/CPU/test-subtensor-insert-multiple-uses.mlir
  MLIR :: Integration/Dialect/Linalg/CPU/test-subtensor-insert.mlir
  MLIR :: Integration/Dialect/Linalg/CPU/test-tensor-e2e.mlir
  MLIR :: Integration/Dialect/Linalg/CPU/test-tensor-matmul.mlir
  MLIR :: Integration/Dialect/Memref/cast-runtime-verification.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/concatenate.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/dense_output.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/dense_output_bf16.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/dense_output_f16.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_abs.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_binary.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_cast.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_codegen_dim.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_codegen_foreach.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_complex32.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_complex64.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_complex_ops.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_constant_to_sparse_tensor.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_conv_1d_nwc_wcf.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_conv_2d.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_conv_2d_nhwc_hwcf.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_conv_3d.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_conv_3d_ndhwc_dhwcf.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_conversion.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_conversion_dyn.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_conversion_ptr.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_conversion_sparse2dense.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_conversion_sparse2sparse.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_dot.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_expand.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_file_io.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_filter_conv2d.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_flatten.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_foreach_slices.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_index.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_index_dense.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_insert_1d.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_insert_2d.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_insert_3d.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_matmul.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_matrix_ops.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_matvec.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_mttkrp.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_out_mult_elt.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_out_reduction.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_out_simple.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_pack.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_quantized_matmul.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_re_im.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_reduce_custom.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_reduce_custom_prod.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_reductions.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_reductions_prod.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_reshape.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_rewrite_push_back.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_rewrite_sort.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_rewrite_sort_coo.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_sampled_matmul.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_sampled_mm_fusion.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_scale.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_scf_nested.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_select.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_sign.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_sorted_coo.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_spmm.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_storage.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_sum.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_sum_bf16.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_sum_c32.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_sum_f16.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_tanh.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_tensor_mul.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_tensor_ops.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_transpose.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_unary.mlir
  MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_vector_ops.mlir
  MLIR :: Integration/Dialect/SparseTensor/python/test_SDDMM.py
  MLIR :: Integration/Dialect/SparseTensor/python/test_SpMM.py
  MLIR :: Integration/Dialect/SparseTensor/python/test_elementwise_add_sparse_output.py
  MLIR :: Integration/Dialect/SparseTensor/python/test_output.py
  MLIR :: Integration/Dialect/SparseTensor/python/test_stress.py
  MLIR :: Integration/Dialect/SparseTensor/taco/test_MTTKRP.py
  MLIR :: Integration/Dialect/SparseTensor/taco/test_SDDMM.py
  MLIR :: Integration/Dialect/SparseTensor/taco/test_SpMM.py
  MLIR :: Integration/Dialect/SparseTensor/taco/test_SpMV.py
  MLIR :: Integration/Dialect/SparseTensor/taco/test_Tensor.py
  MLIR :: Integration/Dialect/SparseTensor/taco/test_scalar_tensor_algebra.py
  MLIR :: Integration/Dialect/SparseTensor/taco/test_simple_tensor_algebra.py
  MLIR :: Integration/Dialect/SparseTensor/taco/test_tensor_complex.py
  MLIR :: Integration/Dialect/SparseTensor/taco/test_tensor_types.py
  MLIR :: Integration/Dialect/SparseTensor/taco/test_tensor_unary_ops.py
  MLIR :: Integration/Dialect/SparseTensor/taco/test_true_dense_tensor_algebra.py
  MLIR :: Integration/Dialect/SparseTensor/taco/unit_test_tensor_core.py
  MLIR :: Integration/Dialect/SparseTensor/taco/unit_test_tensor_io.py
  MLIR :: Integration/Dialect/SparseTensor/taco/unit_test_tensor_utils.py
  MLIR :: Integration/Dialect/Standard/CPU/test-ceil-floor-pos-neg.mlir
  MLIR :: Integration/Dialect/Standard/CPU/test_subview.mlir
  MLIR :: Integration/Dialect/Vector/CPU/AMX/test-mulf-full.mlir
  MLIR :: Integration/Dialect/Vector/CPU/AMX/test-mulf.mlir
  MLIR :: Integration/Dialect/Vector/CPU/AMX/test-muli-ext.mlir
  MLIR :: Integration/Dialect/Vector/CPU/AMX/test-muli-full.mlir
  MLIR :: Integration/Dialect/Vector/CPU/AMX/test-muli.mlir
  MLIR :: Integration/Dialect/Vector/CPU/AMX/test-tilezero-block.mlir
  MLIR :: Integration/Dialect/Vector/CPU/AMX/test-tilezero.mlir
  MLIR :: Integration/Dialect/Vector/CPU/X86Vector/test-dot.mlir
  MLIR :: Integration/Dialect/Vector/CPU/X86Vector/test-inline-asm-vector-avx512.mlir
  MLIR :: Integration/Dialect/Vector/CPU/X86Vector/test-mask-compress.mlir
  MLIR :: Integration/Dialect/Vector/CPU/X86Vector/test-rsqrt.mlir
  MLIR :: Integration/Dialect/Vector/CPU/X86Vector/test-sparse-dot-product.mlir
  MLIR :: Integration/Dialect/Vector/CPU/X86Vector/test-vp2intersect-i32.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-0-d-vectors.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-broadcast.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-compress.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-constant-mask.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-contraction.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-create-mask-v4i1.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-create-mask.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-expand.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-extract-strided-slice.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-flat-transpose-col.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-flat-transpose-row.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-fma.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-gather.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-index-vectors.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-insert-strided-slice.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-maskedload.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-maskedstore.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-matrix-multiply-col.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-matrix-multiply-row.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-outerproduct-f32.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-outerproduct-i64.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-print-int.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-realloc.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-reductions-f32-reassoc.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-reductions-f32.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-reductions-f64-reassoc.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-reductions-f64.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-reductions-i32.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-reductions-i4.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-reductions-i64.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-reductions-si4.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-reductions-ui4.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-scan.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-scatter.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-shape-cast.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-shuffle.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-sparse-dot-matvec.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-sparse-saxpy-jagged-matvec.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-transfer-read-1d.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-transfer-read-2d.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-transfer-read-3d.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-transfer-read.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-transfer-to-loops.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-transfer-write.mlir
  MLIR :: Integration/Dialect/Vector/CPU/test-transpose.mlir

Testing Time: 0.29s
  Unsupported:  31
  Passed     :   5
  Failed     : 186

Differential Revision: https://reviews.llvm.org/D143970
2023-02-13 18:30:52 -08:00
Peiming Liu
ce9ce66b8d [mlir][sparse] fix a memory leakage when converting from a tensor slice
Reviewed By: aartbik

Differential Revision: https://reviews.llvm.org/D143929
2023-02-13 22:44:12 +00:00
Markus Böck
161b9d741a [mlir] Make the vast majority of integration and runner tests work on Windows
This patch contains the changes required to make the vast majority of integration and runner tests run on Windows.
Historically speaking, the JIT support for Windows has been lacking behind, but recent versions of ORC JIT have now caught up and works for basically all examples in repo.

Sadly due to these tests previously not working on Windows, basically all of them are making unix-like assumptions about things like filenames, paths, shell syntax etc.
This patch fixes all these issues in one big swoop and enables Windows support for the vast majority of integration tests.

More specifically, following changes had to be done:
* The various JIT runners used paths to the runtime libraries that assumed a Unix toolchain layout and filenames. I abstracted the specific path and filename of these runtime libraries away by making the paths to the runtime libraries be passed from cmake into lit. This now also allows a much more convenient syntax: `--shared-libs=%mlir_c_runner_utils` instead of `--shared-libs=%mlir_lib_dir/lib/libmlir_c_runner_utils%shlibext`
* Some tests using python set environment variables using the `ENV=VALUE cmd` format. This works on Unix, but on Windows it has to prefixed using `env ENV=VALUE cmd`
* Some tests used C functions that are simply not available or exported on Windows (`fabsf`, `aligned_alloc`). These tests have either been adjusted or explicitly marked as `UNSUPPORTED`

Some tests remain disabled on Windows as before:
* In SparseTensor some tests have non-trivial logic for finding the runtime libraries which seems to be required for the use of emulators. I do not have the time to port these so I simply kept them disabled
* Some tests requiring special hardware which I simply cannot test remain disabled on Windows. These include usage of AVX512 or AMX

The tests for `mlir-vulkan-runner` and `mlir-spirv-runner` all work now as well and so do the vast majority of `mlir-cpu-runner`.

Differential Revision: https://reviews.llvm.org/D143925
2023-02-13 22:24:20 +01:00
Peiming Liu
dc6427d687 [mlir][sparse] implement lowering rules for sparse_tensor::unpack
Reviewed By: aartbik

Differential Revision: https://reviews.llvm.org/D143672
2023-02-11 01:05:46 +00:00
Jim Kitchen
81d0d2b2a0 [mlir][sparse] Sparse reduction in lex order no longer produces dense output
Previously, when performing a reduction on a sparse tensor, the result
would be different depending on iteration order. For expanded access pattern,
an empty row would contribute no entry in the output. For lex ordering, the
identity would end up in the output.

This code changes that behavior and keeps track of whether any entries were
actually reduced in lex ordering, making the output consistent between the
two iteration styles.

Differential Revision: https://reviews.llvm.org/D142050
2023-02-10 13:09:28 -06:00
Aart Bik
c55e6afe81 [mlir][sparse] fix integration test with "VLA" run
Reviewed By: Peiming

Differential Revision: https://reviews.llvm.org/D143674
2023-02-09 12:50:24 -08:00
Andrzej Warzynski
bfe4ce3f83 [mlir][sparse] Port the remaining integration tests to use SVE
This patch updates the remaining SparseCompiler integration tests to
target SVE when available.

Two tests will require some investigation in the future:
  * sparse_matmul.mlir
  * sparse_tanh.mlir
The former passes regardless - that's due to how `CHECK` lines are
defined. The latter fails when SVE is enabled, but passes when it's
disabled. I marked it as UNSUPPORTED as there is no mechanism to XFAIL a
test conditionally. Also, see [1] for more details.

[1] https://github.com/llvm/llvm-project/issues/60626

Differential Revision: https://reviews.llvm.org/D143514
2023-02-09 10:14:53 +00:00
bixia1
a150766880 [mlir][sparse] Implement hybrid quick sort for sparse_tensor.sort.
Reviewed By: aartbik

Differential Revision: https://reviews.llvm.org/D143227
2023-02-08 14:06:31 -08:00
Peiming Liu
0352690421 [mlir][sparse] make foreach operation support sparse tensor slices.
Reviewed By: aartbik

Differential Revision: https://reviews.llvm.org/D140713
2023-02-08 18:58:35 +00:00