Fix a regression caused by https://reviews.llvm.org/D158012. Failing
bot:
* https://lab.llvm.org/buildbot/#/builders/179/builds/7122
Note that both `RUN` lines in the affected file were previously
tested with similar configuraiton (_with_ and _without_ vectorisation).
This change restores that, though the new setting (from D158012) is
used, i.e.
* with direct IR generation, `enable-runtime-library=true`.
This is sufficient to make the test pass and allows us to investigate
the root cause offline. Issue reported here:
https://github.com/llvm/llvm-project/issues/64727
Reland of the original patch after updating the Python binding tests,
a few CUDA/GPU MLIR tests, and ensuring the assembly format is
round-trippable.
This patch splits the lowering of vector.print into first converting
an n-D print into a loop of scalar prints of the elements, then a second
pass that converts those scalar prints into the runtime calls. The
former is done in VectorToSCF and the latter in VectorToLLVM.
The main reason for this is to allow printing scalable vector types,
which are not possible to fully unroll at compile time, though this
also avoids fully unrolling very large vectors.
To allow VectorToSCF to add the necessary punctuation between vectors
and elements, a "punctuation" attribute has been added to vector.print.
This abstracts calling the runtime functions such as printNewline(),
without leaking the LLVM details into the higher abstraction levels.
For example:
vector.print punctuation <comma>
lowers to
llvm.call @printComma() : () -> ()
The output format and runtime functions remain the same, which avoids
the need to alter a large number of tests (aside from the pipelines).
Reviewed By: awarzynski, c-rhodes, aartbik
Differential Revision: https://reviews.llvm.org/D156519
CHANGES SINCE THE ORIGINAL VERSION
----------------------------------
The default test set-up was extracted from
* SparseTensor/CPU/lit.local.cfg.
and duplicated in all tests. This is to support downstream users that
don't use these local LIT config files.
SUMMARY OF CHANGES
------------------
This patch aims to reduce test duplication. This is a direct follow-up of:
1. https://reviews.llvm.org/D155403 (test duplication), and
2. https://reviews.llvm.org/D155405 (code re-use),
All SVE/VLA tests are now enabled _conditionally_ and refactored to use
`mlir-cpu-runner` rather than `lli`. The former helps with test
duplication and the latter with code re-use.
A few additional refactoring changes are included.
1. The reduce verbosity, long runtime library names like:
%mlir_native_utils_lib_dir/libmlir_c_runner_utils%shlibext
are replaced with:
%mlir_c_runner_utils
2. In order to keep the code and the comments in sync, and to maintain
consistency across the tests, the following:
enable-runtime-library=true
is swapped with (and vice-versa):
enable-runtime-library=false
Note that this change won't affect test coverage. Only few tests
required such update.
3. A VLS vectorization `RUN` line is added in tests where there was a
VLA/VLS `RUN` line, but no VLS `RUN` line (with a few exceptions of
tests that only contained one `RUN` line to begin with).
4. A few test variables are renamed/added. Most notable example:
* %{options}` --> %{sparse_compiler_opts}
TEST RUNTIME IMPROVEMENT
------------------------
Tl;Dr This change improves test execution time by ~25%.
At the moment, the following `llvm-lit` invocation takes ~7.30s on my
AArch64 workstation (with SVE):
llvm-lit <llvm-project>/mlir/test/Integration/Dialect/SparseTensor/CPU/
This timing doesn't change no matter what the value of the following
CMake variable is (that should disable some tests):
MLIR_RUN_ARM_SVE_TESTS
With this patch, the execution time will indeed depend on the value of
the above CMake variable:
* with `MLIR_RUN_ARM_SVE_TESTS=true` the timing remains intact,
* with `MLIR_RUN_ARM_SVE_TESTS=false` the timing drops to ~5.40s (~25%
improvement).
This is expected:
* on average there are 4 `RUN` lines per test,
* _without this change_ (and with `MLIR_RUN_ARM_SVE_TESTS=false`) the
4th `RUN` line would in most cases duplicate the 3rd `RUN` line,
* _with this change) (and with `MLIR_RUN_ARM_SVE_TESTS=false`) the
4th `RUN` line becomes empty.
PATCH SIZE
----------
While rather large and touching many files, most changes in this patch
are rather mechanical. All test configurations have been preserved and
only in a handful of cases new `RUN` lines added.
Differential Revision: https://reviews.llvm.org/D156625
Reland of the original patch after updating the Python binding tests and
a few CUDA/GPU MLIR tests.
This patch splits the lowering of vector.print into first converting
an n-D print into a loop of scalar prints of the elements, then a second
pass that converts those scalar prints into the runtime calls. The
former is done in VectorToSCF and the latter in VectorToLLVM.
The main reason for this is to allow printing scalable vector types,
which are not possible to fully unroll at compile time, though this
also avoids fully unrolling very large vectors.
To allow VectorToSCF to add the necessary punctuation between vectors
and elements, a "punctuation" attribute has been added to vector.print.
This abstracts calling the runtime functions such as printNewline(),
without leaking the LLVM details into the higher abstraction levels.
For example:
vector.print <comma>
lowers to
llvm.call @printComma() : () -> ()
The output format and runtime functions remain the same, which avoids
the need to alter a large number of tests (aside from the pipelines).
Reviewed By: awarzynski, c-rhodes, aartbik
Differential Revision: https://reviews.llvm.org/D156519
SUMMARY OF CHANGES
------------------
This patch aims to reduce test duplication and to improve code re-use in
SparseTensor integration tests for CPU. This is a direct follow-up of:
1. https://reviews.llvm.org/D155403 (test duplication), and
2. https://reviews.llvm.org/D155405 (code re-use),
The key logic for this patch is implemented in:
* SparseTensor/CPU/lit.local.cfg.
Essentially, the set-up that used to be repeated across all test files
has been extracted into a common LIT configuration file. This makes code
re-use straightforward.
All SVE/VLA tests are now enabled _conditionally_ and refactored to use
`mlir-cpu-runner` rather than `lli`. The former helps with test
duplication and the latter with code re-use.
A few additional refactoring changes are included.
1. The reduce verbosity, long runtime library names like:
%mlir_native_utils_lib_dir/libmlir_c_runner_utils%shlibext
are replaced with:
%mlir_c_runner_utils
2. In order to keep the code and the comments in sync, and to maintain
consistency across the tests, the following:
enable-runtime-library=true
is swapped with (and vice-versa):
enable-runtime-library=false
Note that this change won't affect test coverage. Only few tests
required such update.
3. A VLS vectorization `RUN` line is added in tests where there was a
VLA/VLS `RUN` line, but no VLS `RUN` line (with a few exceptions of
tests that only contained one `RUN` line to begin with).
4. A few test variables are renamed/added. Most notable example:
* %{options}` --> %{sparse_compiler_opts}
TEST RUNTIME IMPROVEMENT
------------------------
Tl;Dr This change improves test execution time by ~25%.
At the moment, the following `llvm-lit` invocation takes ~7.30s on my
AArch64 workstation (with SVE):
llvm-lit <llvm-project>/mlir/test/Integration/Dialect/SparseTensor/CPU/
This timing doesn't change no matter what the value of the following
CMake variable is (that should disable some tests):
MLIR_RUN_ARM_SVE_TESTS
With this patch, the execution time will indeed depend on the value of
the above CMake variable:
* with `MLIR_RUN_ARM_SVE_TESTS=true` the timing remains intact,
* with `MLIR_RUN_ARM_SVE_TESTS=false` the timing drops to ~5.40s (~25%
improvement).
This is expected:
* on average there are 4 `RUN` lines per test,
* _without this change_ (and with `MLIR_RUN_ARM_SVE_TESTS=false`) the
4th `RUN` line would in most cases duplicate the 3rd `RUN` line,
* _with this change) (and with `MLIR_RUN_ARM_SVE_TESTS=false`) the
4th `RUN` line becomes empty.
PATCH SIZE
----------
While rather large and touching many files, most changes in this patch
are rather mechanical. All test configurations have been preserved and
only in a handful of cases new `RUN` lines added.
Differential Revision: https://reviews.llvm.org/D156625
With the recent addition of "-mattr" and "-march" to the list of options
supported by mlir-cpu-runner [1], the SVE integration
tests can be updated to use mlir-cpu-runner instead of lli. This will
allow better code re-use and more consistency
This patch updates 2 tests to demonstrate the new logic. The remaining
tests will be updated in the follow-up patches.
[1] https://reviews.llvm.org/D146917
Depends on D155403
Differential Revision: https://reviews.llvm.org/D155405
This patch updates one SparseTensor integration test so that the VLA
vectorisation is run conditionally based on the value of the
MLIR_RUN_ARM_SME_TESTS CMake variable.
This change opens the path to reduce the duplication of RUN lines in
"mlir/test/Integration/Dialect/SparseTensor/CPU/". ATM, there are
usually 2 RUN lines to test vectorization in SparseTensor integration
tests:
* one for VLS vectorisation,
* one for VLA vectorisation whenever that's available and which
reduces to VLS vectorisation when VLA is not supported.
When VLA is not available, VLS vectorisation is verified twice. This
duplication should be avoided - integration test are relatively
expansive to run.
This patch makes sure that the 2nd vectorisation RUN line becomes:
```
if (SVE integration tests are enabled)
run VLA vectorisation
else
return
```
This logic is implemented using LIT's (relatively new) conditional
substitution [1]. It enables us to guarantee that all RUN lines are
unique and that the VLA vectorisation is only enabled when supported.
This patch updates only 1 test to set-up and to demonstrate the logic.
Subsequent patches will update the remaining tests.
[1] https://www.llvm.org/docs/TestingGuide.html
Differential Revision: https://reviews.llvm.org/D155403
(1) without the check, the results may silently be wrong, so check is needed
(2) add pruning step to guarantee 2:4 property
Note, in the longer run, we may want to split out the pruning step somehow,
or make it optional.
Reviewed By: K-Wu
Differential Revision: https://reviews.llvm.org/D155320
When targeting NVIDIA GPUs, seeing the generated PTX is important. Currently, we don't have simple way to do it.
This work adds dump-ptx to gpu-to-cubin pass. One can use it like `gpu-to-cubin{chip=sm_90 features=+ptx80 dump-ptx}`.
Reviewed By: nicolasvasilache
Differential Revision: https://reviews.llvm.org/D155166
This might simplify frontend implementation by avoiding recomputation for the same value.
Reviewed By: aartbik
Differential Revision: https://reviews.llvm.org/D154244
We recently fixed a bug in "sparsifying" such reductions, since
it incorrectly changed this into reductions over stored elements
only , which only works for add/sub/or/xor. However, we still want
to be able to "sparsify" the reductions even in the general case,
and this is a first step by rewriting them into a custom reduction
that feeds in the implicit zeros. NOTE HOWEVER, that in the long run
we want to do this better and feed in any implicit zero only ONCE
for efficiency.
Reviewed By: Peiming
Differential Revision: https://reviews.llvm.org/D152580
Document better that unary/binary may only feed to the output
or the input of a custom reduction (not even a regular reduction
since it may have "no value"!). Also fixes a bug when present
branch is empty and feeds into custom reduction.
Reviewed By: Peiming
Differential Revision: https://reviews.llvm.org/D152224
Note that by sparse compiler convention, dense output
is zerod out when not set, so complement results in
zeros where elements were present.
Reviewed By: wrengr
Differential Revision: https://reviews.llvm.org/D152046
Formerly, we accepted and/prod reductions as a standard
reduction but these change the semantics after sparsification
by not looking at implicit zeros. Therefore, we only accept
standard reductions that are insensitive to implicit vs.
explicit zeros, and leave the more complex reductions to
the sparse_tensor.reduce custom reduction implementation.
Reviewed By: Peiming
Differential Revision: https://reviews.llvm.org/D151929
This is a major step along the way towards the new STEA design. While a great deal of this patch is simple renaming, there are several significant changes as well. I've done my best to ensure that this patch retains the previous behavior and error-conditions, even though those are at odds with the eventual intended semantics of the `dimToLvl` mapping. Since the majority of the compiler does not yet support non-permutations, I've also added explicit assertions in places that previously had implicitly assumed it was dealing with permutations.
Reviewed By: aartbik
Differential Revision: https://reviews.llvm.org/D151505
This is an ongoing series of commits that are reformatting our
Python code.
Reformatting is done with `black`.
If you end up having problems merging this commit because you
have made changes to a python file, the best way to handle that
is to run git checkout --ours <yourfile> and then reformat it
with black.
If you run into any problems, post to discourse about it and
we will try to help.
RFC Thread below:
https://discourse.llvm.org/t/rfc-document-and-standardize-python-code-style
Differential Revision: https://reviews.llvm.org/D150782
(1) minor bug fix in copy back [always nice to run stuff ;-)]
(2) run with and without lib (even though some fall back to CPU)
Reviewed By: wrengr
Differential Revision: https://reviews.llvm.org/D151507
