[mlir] Make the vast majority of integration and runner tests work on Windows

[zero9178]

Summary

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 and implemented search logic in lit to find these isntead. 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.

[mehdi_amini]

Nice!

[aartbik]

Can we revert this?
Integration tests are broken

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

....

Failed Tests (153):

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/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/Standard/CPU/test-ceil-floor-pos-neg.mlir
MLIR :: Integration/Dialect/Standard/CPU/test_subview.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: 0.46s

Unsupported:  64
Passed     :   5
Failed     : 153

[zero9178]

Hello Aart!

I am sorry that this patch is causing you trouble. Do you happen to know as to why the changes are seemingly breaking, what I am assuming to be your develop environment?
More specifically I am wondering whether your cmake options or maybe version do not play well with the changes here.
The list of failed tests seems to include basically all of them, so I am thinking its some environment issue. Furthermore, all build bots seemingly had no problem running all these tests and neither did I on both my Windows and Linux machine.
This includes eg. the AMD build bot which did run all the integration tests that seemingly failed on your machine https://lab.llvm.org/buildbot/#/builders/220/builds/15586

[aartbik]

In D143925#4124891, @zero9178 wrote:

Hello Aart!

I am sorry that this patch is causing you trouble. Do you happen to know as to why the changes are seemingly breaking, what I am assuming to be your develop environment?
More specifically I am wondering whether your cmake options or maybe version do not play well with the changes here.
The list of failed tests seems to include basically all of them, so I am thinking its some environment issue. Furthermore, all build bots seemingly had no problem running all these tests and neither did I on both my Windows and Linux machine.
This includes eg. the AMD build bot which did run all the integration tests that seemingly failed on your machine https://lab.llvm.org/buildbot/#/builders/220/builds/15586

Thanks for your prompt reply! I am one of the original authors of the integration tests, and have been running them since I started the suite, always the same way, and they started only breaking after this change. Not too many people (or bots) run the full integration suite, so I am more likely to find issues than our automated ways, unfortunately. Lastly, note that I also do rotation duties for the Google repo, and this change most likely broke our bazel build setup (but that is *not* the reason for reverting, to be clear, the reason for reverting was a plain Linux vanilla setup breakage).

To give you more details, this is my config, for example (an asan one)

cmake -G Ninja ../llvm \
 -DLLVM_ENABLE_PROJECTS=mlir \
 -DLLVM_BUILD_EXAMPLES=ON \
 -DLLVM_TARGETS_TO_BUILD="host" \
 -DCMAKE_BUILD_TYPE=Release \
 -DLLVM_ENABLE_WARNINGS=ON \
 -DLLVM_ENABLE_PEDANTIC=ON \
 -DLLVM_ENABLE_ASSERTIONS=ON \
 -DLLVM_USE_SANITIZER=Address \
 -DMLIR_RUN_AMX_TESTS=OFF \
 -DMLIR_RUN_X86VECTOR_TESTS=OFF \
 -DMLIR_RUN_ARM_SVE_TESTS=OFF \
 -DMLIR_INCLUDE_INTEGRATION_TESTS=ON \
 -DMLIR_INCLUDE_TESTS=ON \
 -DBUILD_SHARED_LIBS=OFF \
 -DMLIR_ENABLE_BINDINGS_PYTHON=OFF \
 -DCMAKE_C_COMPILER=clang -DCMAKE_CXX_COMPILER=clang++ -DLLVM_ENABLE_LLD=ON

and this is a typical run command

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

[mehdi_amini]

Maybe you can get some log output of the failures?

[aartbik]

In D143925#4125090, @mehdi_amini wrote:

Maybe you can get some log output of the failures?

Yeah, always a good idea (sorry -it has been a long day here-)

Here is the output on main, using the setup given earlier, *after* the revert, so all is well.

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

[0/1] Running lit suite /usr/local/google/home/ajcbik/LLVM/llvm-project/mlir/test/Integration

Testing Time: 38.38s
  Unsupported:  64
  Passed     : 158

Then, rolling back to a change *before* the revert, with some of the logging output below.
Note that I see a strange literal ,$<TARGET_FILE:mlir_runner_utils> in the RUN command.
It is not impossible something is wrong in my setup, but, again, please note I have been running
this from the very start of the suite ;-)

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

[0/1] Running lit suite /usr/local/google/home/ajcbik/LLVM/llvm-project/mlir/test/Integration
-- Testing: 222 tests, 12 workers --
Testing:
FAIL: MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_conversion_sparse2dense.mlir (1 of 222)
******************** TEST 'MLIR :: Integration/Dialect/SparseTensor/CPU/sparse_conversion_sparse2dense.mlir' FAILED ********************
Script:
--
: 'RUN: at line 8';   /usr/local/google/home/ajcbik/LLVM/llvm-project/build_asan/bin/mlir-opt /usr/local/google/home/ajcbik/LLVM/llvm-project/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_conversion_sparse2dense.mlir --sparse  -compiler=enable-runtime-library=true | /usr/local/google/home/ajcbik/LLVM/llvm-project/build_asan/bin/mlir-cpu-runner -e entry -entry-point-result=void -shared-libs=$<TARGET_FILE:mlir_c_runner_utils>,$<TARGET_FILE:mlir_runner_utils> | /usr/local/google/home/ajcbik/LLVM/llvm-project/build_asan/bin/FileCheck /usr/local/google/home/ajcbik/LLVM/llvm-project/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_conversion_sparse2dense.mlir

 ...

Testing Time: 3.73s
  Unsupported:  64
  Passed     :   5
  Failed     : 153

[mehdi_amini]

In D143925#4125120, @aartbik wrote:

Then, rolling back to a change *before* the revert, with some of the logging output below.
Note that I see a strange literal ,$<TARGET_FILE:mlir_runner_utils> in the RUN command.

Thanks! That's likely be helpful, the $<TARGET_FILE:mlir_runner_utils> seems like CMake internal not being expanded. It could be a matter of different CMake version or some build flags (like -DBUILD_SHARED_LIBS or other settings)

[zero9178]

This seems likely to be a cmake issue indeed. What cmake version are you using?
I tested it a second ago with 3.15 and 3.20 on Linux with the same configure options as you posted and 3.25 on Windows and they all work.
3.13 is the oldest that MLIR supposedly allows (although with deprecation warning) but that threw some errors so couldn't test that old of a version.

Did you also attempt to fully reconfigure the project, as in completetely delete the cmake build directory and reconfigure? I'd hope that'd not be necessary but you never know with cmake :(

[aartbik]

In D143925#4125704, @zero9178 wrote:

This seems likely to be a cmake issue indeed. What cmake version are you using?
I tested it a second ago with 3.15 and 3.20 on Linux with the same configure options as you posted and 3.25 on Windows and they all work.

cmake -version
cmake version 3.25.1

CMake suite maintained and supported by Kitware (kitware.com/cmake).

[awarzynski]

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_sampled_matmul.mlir

27

Could you update this (and other similar REDEFINEs in mlir/test/Integration/Dialect/SparseTensor/CPU/) as well? Thanks!

[zero9178]

Managed to reproduce the error. I basically had to copy your exact cmake command. Only then could I use the check-mlir-integration target. Running just check-mlir works without issues. I am confused why check-mlir-integration is not available in any of my other build configs, but at least I can test and reproduce it.

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_sampled_matmul.mlir

27

These paths use %mlir_native_utils_lib_dir which is not always substituted to the same as %mlir_lib_dir is. In particular, these may be set differently when using enumlators to execute the code. Since I'd certainly break such setups and I am unable to test these I left these as is and have disabled the SparseTensor tests on Windows

[zero9178]

Don't try to create the lit.site.cfg.py file in two steps, but teach configure_lit_site_cfg how to evaluate generator expressions instead.

The input filename to configure_lit_site_cfg is recorded and put into a global map for llvm-lit, allowing it to be run on subdirectories of a testsuite and still find the lit.site.cfg.py required. Problem was, that the patch doing the config generation in two steps, recorded lit.site.cfg.py.in in this global map, as that is what was passed to configure_lit_site_cfg. check-mlir-integration would therefore read in that file instead of lit.site.cfg.py and the tests would be broken.

[mehdi_amini]

Can you split the infrastructure change (CMake, lit config, etc.) to a separate patch? Seems like another issue you're addressing there.

[zero9178]

Move logic from cmake into lit. Lit now searches for the runtime libraries by simply looking for the file in SHLIBDIR (a variable set to the directory containing the shared libraries on the platform, set by configure_lit_site_cfg) with either no prefix or lib as prefix and the platforms shared library suffix.

The advantages over this approach over the cmake approach is that it 1) uses Python code not cmake 2) therefore works with bazel as well 3) and works correctly with multi-config generators on cmake (which my previous approach did not).

[zero9178]

@mehdi_amini PTAL

[awarzynski]

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_sampled_matmul.mlir

27

Ack, thanks for the explanation!

[mehdi_amini]

mlir/test/lit.cfg.py

46

Comment this maybe?

[zero9178]

Address review comments

[aartbik]

The change now sticks on linux/cmake, but the bazel configuration I am monitoring is completely broken with this substitution mechanism.
Do you have any pointers for me on where to start debugging this?

I see a non-substituted command line

1. mlir-opt /usr/local/google/_blaze_ajcbik/77adac8990317f04651682107287f0d3/execroot/google3/blaze-out/k8-fastbuild/bin/third_party/llvm/llvm-project/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_index_dense.mlir.test.runfiles/google3/third_party/llvm/llvm-project/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_index_dense.mlir --sparse-compiler=enable-runtime-library=false | mlir-cpu-runner -e entry -entry-point-result=void -shared-libs=%mlir_c_runner_utils | FileCheck /usr/local/google/_blaze_ajcbik/77adac8990317f04651682107287f0d3/execroot/google3/blaze-out/k8-fastbuild/bin/third_party/llvm/llvm-project/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_index_dense.mlir.test.runfiles/google3/third_party/llvm/llvm-project/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_index_dense.mlir

[zero9178]

In D143925#4129879, @aartbik wrote:

The change now sticks on linux/cmake, but the bazel configuration I am monitoring is completely broken with this substitution mechanism.
Do you have any pointers for me on where to start debugging this?

I see a non-substituted command line

1. mlir-opt /usr/local/google/_blaze_ajcbik/77adac8990317f04651682107287f0d3/execroot/google3/blaze-out/k8-fastbuild/bin/third_party/llvm/llvm-project/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_index_dense.mlir.test.runfiles/google3/third_party/llvm/llvm-project/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_index_dense.mlir --sparse-compiler=enable-runtime-library=false | mlir-cpu-runner -e entry -entry-point-result=void -shared-libs=%mlir_c_runner_utils | FileCheck /usr/local/google/_blaze_ajcbik/77adac8990317f04651682107287f0d3/execroot/google3/blaze-out/k8-fastbuild/bin/third_party/llvm/llvm-project/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_index_dense.mlir.test.runfiles/google3/third_party/llvm/llvm-project/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_index_dense.mlir

The only change that it ought to require is for Bazel to also substitute @SHLIBDIR@ within lit.site.cfg.py.in correctly. It should expand to the directory where the runtime libraries are contained in. In the cmake build that'd be the LLVM_SHLIB_OUTPUT_INTDIR variable

[aartbik]

Our set up is a little different, but I got a running again. Thanks!

[aartbik]

In D143925#4130103, @aartbik wrote:

Our set up is a little different, but I got a running again. Thanks!

Note that it also seems to have broken our bazel build bots

https://buildkite.com/llvm-project/upstream-bazel/builds/54269#018656fb-2bdc-4994-b90f-6a82289b5baa

mlir/include/mlir/ExecutionEngine/RunnerUtils.h

 #else
 // Non-windows: use visibility attributes.
 #define MLIR_RUNNERUTILS_EXPORT __attribute__((visibility("default")))
 #endif // _WIN32
 
 #include <assert.h>
 #include <cmath>
 #include <complex>
+#include <iomanip>
 #include <iostream>
 
 #include "mlir/ExecutionEngine/CRunnerUtils.h"
 
 template <typename T, typename StreamType>
 void printMemRefMetaData(StreamType &os, const DynamicMemRefType<T> &v) {
-  os << "base@ = " << reinterpret_cast<void *>(v.data) << " rank = " << v.rank
-     << " offset = " << v.offset;
+  // Make the printed pointer format platform independent by casting it to an
+  // integer and manually formatting it to a hex with prefix as tests expect.
+  os << "base@ = " << std::hex << std::showbase
+     << reinterpret_cast<std::intptr_t>(v.data) << std::dec << std::noshowbase
+     << " rank = " << v.rank << " offset = " << v.offset;
   auto print = [&](const int64_t *ptr) {
     if (v.rank == 0)
       return;
     os << ptr[0];
     for (int64_t i = 1; i < v.rank; ++i)
       os << ", " << ptr[i];
   };
   os << " sizes = [";

mlir/test/CMakeLists.txt

 add_subdirectory(CAPI)
 add_subdirectory(lib)
 
 if (MLIR_ENABLE_BINDINGS_PYTHON)
   add_subdirectory(python)
 endif()
 
+if (MLIR_ENABLE_SPIRV_CPU_RUNNER)
+  add_subdirectory(mlir-spirv-cpu-runner)
+endif()
+
 # Provide the MLIR CMake module dir so that the out of tree Standalone
 # dialect and can add it to the module path.
 set(MLIR_CMAKE_DIR
   "${CMAKE_BINARY_DIR}/lib${LLVM_LIBDIR_SUFFIX}/cmake/mlir")
 
 # Passed to lit.site.cfg.py.in to set up the path where to find libraries.
 set(MLIR_LIB_DIR ${CMAKE_LIBRARY_OUTPUT_DIRECTORY})
 
llvm_canonicalize_cmake_booleans(
   MLIR_ENABLE_VULKAN_RUNNER
   MLIR_INCLUDE_INTEGRATION_TESTS
   MLIR_RUN_AMX_TESTS
   MLIR_RUN_CUDA_TENSOR_CORE_TESTS
   MLIR_RUN_X86VECTOR_TESTS
   MLIR_RUN_ARM_SVE_TESTS
   )
 
+set(MLIR_RUNNER_UTILS "$<TARGET_FILE:mlir_runner_utils>")
+set(MLIR_C_RUNNER_UTILS "$<TARGET_FILE:mlir_c_runner_utils>")
+set(MLIR_ASYNC_RUNTIME "$<TARGET_FILE:mlir_async_runtime>")
+
+if (MLIR_ENABLE_VULKAN_RUNNER)
+  set(MLIR_VULKAN_RUNTIME_WRAPPERS "$<TARGET_FILE:vulkan-runtime-wrappers>")
+endif ()
+
+if (MLIR_ENABLE_CUDA_RUNNER)
+  set(MLIR_CUDA_RUNTIME "$<TARGET_FILE:mlir_cuda_runtime>")
+endif ()
+
+if (MLIR_ENABLE_ROCM_RUNNER)
+  set(MLIR_ROCM_RUNTIME "$<TARGET_FILE:mlir_rocm_runtime>")
+endif ()
+
+if (MLIR_ENABLE_SPIRV_CPU_RUNNER)
+  set(MLIR_TEST_SPRIV_CPU_RUNNER_C_WRAPPERS "$<TARGET_FILE:mlir_test_spirv_cpu_runner_c_wrappers>")
+endif ()
+
+# configure below runs at configure time and does not support the use of generator expressions.
+# We therefore use it only to substitute the generator expressions above into the lit.site.cfg.py.in.
 configure_lit_site_cfg(
   ${CMAKE_CURRENT_SOURCE_DIR}/lit.site.cfg.py.in
-  ${CMAKE_CURRENT_BINARY_DIR}/lit.site.cfg.py
+  ${CMAKE_CURRENT_BINARY_DIR}/lit.site.cfg.py.in
   MAIN_CONFIG
   ${CMAKE_CURRENT_SOURCE_DIR}/lit.cfg.py
   )
+# GENERATE runs at generation time (so at the beginning of the build) and substitutes the generator expressions
+# with the actual paths of the target binaries.
+file(GENERATE OUTPUT ${CMAKE_CURRENT_BINARY_DIR}/lit.site.cfg.py
+        INPUT ${CMAKE_CURRENT_BINARY_DIR}/lit.site.cfg.py.in)
+
 configure_lit_site_cfg(
   ${CMAKE_CURRENT_SOURCE_DIR}/Unit/lit.site.cfg.py.in
   ${CMAKE_CURRENT_BINARY_DIR}/Unit/lit.site.cfg.py
   MAIN_CONFIG
   ${CMAKE_CURRENT_SOURCE_DIR}/Unit/lit.cfg.py
   )
 
 set(MLIR_TEST_DEPENDS
if(MLIR_ENABLE_EXECUTION_ENGINE)
     list(APPEND MLIR_TEST_DEPENDS
       toyc-ch6
       toyc-ch7
     )
   endif()
 endif()
 
 if(MLIR_ENABLE_SPIRV_CPU_RUNNER)
-  add_subdirectory(mlir-spirv-cpu-runner)
   list(APPEND MLIR_TEST_DEPENDS
     mlir-spirv-cpu-runner
     mlir_test_spirv_cpu_runner_c_wrappers
   )
 endif()
 
 if(MLIR_ENABLE_VULKAN_RUNNER)
   list(APPEND MLIR_TEST_DEPENDS

mlir/test/Integration/Dialect/Arith/CPU/lit.local.cfg

-import sys
-
-# No JIT on win32.
-if sys.platform == 'win32':
-    config.unsupported = True

mlir/test/Integration/Dialect/Arith/CPU/test-wide-int-emulation-addi-i16.mlir

 // Check that the wide integer addition emulation produces the same result as
 // wide addition. Emulate i16 ops with i8 ops.
 
 // RUN: mlir-opt %s --convert-scf-to-cf --convert-cf-to-llvm --convert-vector-to-llvm \
 // RUN:             --convert-func-to-llvm --convert-arith-to-llvm | \
 // RUN:   mlir-cpu-runner -e entry -entry-point-result=void \
-// RUN:                   --shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:                   --shared-libs=%mlir_c_runner_utils | \
 // RUN:   FileCheck %s --match-full-lines
 
 // RUN: mlir-opt %s --test-arith-emulate-wide-int="widest-int-supported=8" \
 // RUN:             --convert-scf-to-cf --convert-cf-to-llvm --convert-vector-to-llvm \
 // RUN:             --convert-func-to-llvm --convert-arith-to-llvm | \
 // RUN:   mlir-cpu-runner -e entry -entry-point-result=void \
-// RUN:                   --shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:                   --shared-libs=%mlir_c_runner_utils | \
 // RUN:   FileCheck %s --match-full-lines
 
 // Ops in this function *only* will be emulated using i8 types.
 func.func @emulate_addi(%lhs : i16, %rhs : i16) -> (i16) {
   %res = arith.addi %lhs, %rhs : i16
   return %res : i16
 }
 

mlir/test/Integration/Dialect/Arith/CPU/test-wide-int-emulation-cmpi-i16.mlir

 // Check that the wide integer `arith.cmpi` emulation produces the same result as wide
 // `arith.cmpi`. Emulate i16 ops with i8 ops.
 // Ops in functions prefixed with `emulate` will be emulated using i8 types.
 
 // RUN: mlir-opt %s --convert-scf-to-cf --convert-cf-to-llvm --convert-vector-to-llvm \
 // RUN:             --convert-func-to-llvm --convert-arith-to-llvm | \
 // RUN:   mlir-cpu-runner -e entry -entry-point-result=void \
-// RUN:                   --shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:                   --shared-libs=%mlir_c_runner_utils | \
 // RUN:   FileCheck %s --match-full-lines
 
 // RUN: mlir-opt %s --test-arith-emulate-wide-int="widest-int-supported=8" \
 // RUN:             --convert-scf-to-cf --convert-cf-to-llvm --convert-vector-to-llvm \
 // RUN:             --convert-func-to-llvm --convert-arith-to-llvm | \
 // RUN:   mlir-cpu-runner -e entry -entry-point-result=void \
-// RUN:                   --shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:                   --shared-libs=%mlir_c_runner_utils | \
 // RUN:   FileCheck %s --match-full-lines
 
 func.func @emulate_cmpi_eq(%lhs : i16, %rhs : i16) -> (i1) {
   %res = arith.cmpi eq, %lhs, %rhs : i16
   return %res : i1
 }
 
 func.func @check_cmpi_eq(%lhs : i16, %rhs : i16) -> () {

mlir/test/Integration/Dialect/Arith/CPU/test-wide-int-emulation-compare-results-i16.mlir

 // Check that the wide integer emulation produces the same result as wide
 // calculations. Emulate i16 ops with i8 ops.
 
 // RUN: mlir-opt %s --test-arith-emulate-wide-int="widest-int-supported=8" \
 // RUN:             --convert-scf-to-cf --convert-cf-to-llvm --convert-vector-to-llvm \
 // RUN:             --convert-func-to-llvm --convert-arith-to-llvm | \
 // RUN:   mlir-cpu-runner -e entry -entry-point-result=void \
-// RUN:      --shared-libs="%mlir_lib_dir/libmlir_c_runner_utils%shlibext,%mlir_lib_dir/libmlir_runner_utils%shlibext" | \
+// RUN:      --shared-libs="%mlir_c_runner_utils,%mlir_runner_utils" | \
 // RUN:   FileCheck %s
 
 // CHECK-NOT: Mismatch
 
 //===----------------------------------------------------------------------===//
 // Common Utility Functions
 //===----------------------------------------------------------------------===//
 

mlir/test/Integration/Dialect/Arith/CPU/test-wide-int-emulation-constants-i16.mlir

 // Check that the wide integer constant emulation produces the same result as wide
 // constants and that printing works. Emulate i16 ops with i8 ops.
 
 // RUN: mlir-opt %s --test-arith-emulate-wide-int="widest-int-supported=8" \
 // RUN:             --convert-scf-to-cf --convert-cf-to-llvm --convert-vector-to-llvm \
 // RUN:             --convert-func-to-llvm --convert-arith-to-llvm | \
 // RUN:   mlir-cpu-runner -e entry -entry-point-result=void \
-// RUN:                   --shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:                   --shared-libs=%mlir_c_runner_utils | \
 // RUN:   FileCheck %s --match-full-lines --check-prefix=EMULATED
 
 func.func @entry() {
   %cst0 = arith.constant 0 : i16
   func.call @emulate_constant(%cst0) : (i16) -> ()
   func.call @foo(%cst0) : (i16) -> ()
   return
 }

mlir/test/Integration/Dialect/Arith/CPU/test-wide-int-emulation-max-min-i16.mlir

 // Check that the wide integer `arith.max*i`/`min*i` emulation produces the
 // same result as wide ops. Emulate i16 ops with i8 ops.
 // Ops in functions prefixed with `emulate` will be emulated using i8 types.
 
 // RUN: mlir-opt %s --convert-scf-to-cf --convert-cf-to-llvm --convert-vector-to-llvm \
 // RUN:             --convert-func-to-llvm --convert-arith-to-llvm | \
 // RUN:   mlir-cpu-runner -e entry -entry-point-result=void \
-// RUN:                   --shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:                   --shared-libs=%mlir_c_runner_utils | \
 // RUN:   FileCheck %s --match-full-lines
 
 // RUN: mlir-opt %s --test-arith-emulate-wide-int="widest-int-supported=8" \
 // RUN:             --convert-scf-to-cf --convert-cf-to-llvm --convert-vector-to-llvm \
 // RUN:             --convert-func-to-llvm --convert-arith-to-llvm | \
 // RUN:   mlir-cpu-runner -e entry -entry-point-result=void \
-// RUN:                   --shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:                   --shared-libs=%mlir_c_runner_utils | \
 // RUN:   FileCheck %s --match-full-lines
 
 func.func @emulate_maxui(%lhs : i16, %rhs : i16) -> (i16) {
   %res = arith.maxui %lhs, %rhs : i16
   return %res : i16
 }
 
 func.func @check_maxui(%lhs : i16, %rhs : i16) -> () {

mlir/test/Integration/Dialect/Arith/CPU/test-wide-int-emulation-muli-i16.mlir

 // Check that the wide integer multiplication emulation produces the same result as wide
 // multiplication. Emulate i16 ops with i8 ops.
 
 // RUN: mlir-opt %s --convert-scf-to-cf --convert-cf-to-llvm --convert-vector-to-llvm \
 // RUN:             --convert-func-to-llvm --convert-arith-to-llvm | \
 // RUN:   mlir-cpu-runner -e entry -entry-point-result=void \
-// RUN:                   --shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:                   --shared-libs=%mlir_c_runner_utils | \
 // RUN:   FileCheck %s --match-full-lines
 
 // RUN: mlir-opt %s --test-arith-emulate-wide-int="widest-int-supported=8" \
 // RUN:             --convert-scf-to-cf --convert-cf-to-llvm --convert-vector-to-llvm \
 // RUN:             --convert-func-to-llvm --convert-arith-to-llvm | \
 // RUN:   mlir-cpu-runner -e entry -entry-point-result=void \
-// RUN:                   --shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:                   --shared-libs=%mlir_c_runner_utils | \
 // RUN:   FileCheck %s --match-full-lines
 
 // Ops in this function *only* will be emulated using i8 types.
 func.func @emulate_muli(%lhs : i16, %rhs : i16) -> (i16) {
   %res = arith.muli %lhs, %rhs : i16
   return %res : i16
 }
 

mlir/test/Integration/Dialect/Arith/CPU/test-wide-int-emulation-shli-i16.mlir

 // Check that the wide integer `arith.shli` emulation produces the same result as wide
 // `arith.shli`. Emulate i16 ops with i8 ops.
 
 // RUN: mlir-opt %s --convert-scf-to-cf --convert-cf-to-llvm --convert-vector-to-llvm \
 // RUN:             --convert-func-to-llvm --convert-arith-to-llvm | \
 // RUN:   mlir-cpu-runner -e entry -entry-point-result=void \
-// RUN:                   --shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:                   --shared-libs=%mlir_c_runner_utils | \
 // RUN:   FileCheck %s --match-full-lines
 
 // RUN: mlir-opt %s --test-arith-emulate-wide-int="widest-int-supported=8" \
 // RUN:             --convert-scf-to-cf --convert-cf-to-llvm --convert-vector-to-llvm \
 // RUN:             --convert-func-to-llvm --convert-arith-to-llvm | \
 // RUN:   mlir-cpu-runner -e entry -entry-point-result=void \
-// RUN:                   --shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:                   --shared-libs=%mlir_c_runner_utils | \
 // RUN:   FileCheck %s --match-full-lines
 
 // Ops in this function *only* will be emulated using i8 types.
 func.func @emulate_shli(%lhs : i16, %rhs : i16) -> (i16) {
   %res = arith.shli %lhs, %rhs : i16
   return %res : i16
 }
 

mlir/test/Integration/Dialect/Arith/CPU/test-wide-int-emulation-shrsi-i16.mlir

 // Check that the wide integer `arith.shrsi` emulation produces the same result as wide
 // `arith.shrsi`. Emulate i16 ops with i8 ops.
 
 // RUN: mlir-opt %s --convert-scf-to-cf --convert-cf-to-llvm --convert-vector-to-llvm \
 // RUN:             --convert-func-to-llvm --convert-arith-to-llvm | \
 // RUN:   mlir-cpu-runner -e entry -entry-point-result=void \
-// RUN:                   --shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:                   --shared-libs=%mlir_c_runner_utils | \
 // RUN:   FileCheck %s --match-full-lines
 
 // RUN: mlir-opt %s --test-arith-emulate-wide-int="widest-int-supported=8" \
 // RUN:             --convert-scf-to-cf --convert-cf-to-llvm --convert-vector-to-llvm \
 // RUN:             --convert-func-to-llvm --convert-arith-to-llvm | \
 // RUN:   mlir-cpu-runner -e entry -entry-point-result=void \
-// RUN:                   --shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:                   --shared-libs=%mlir_c_runner_utils | \
 // RUN:   FileCheck %s --match-full-lines
 
 // Ops in this function *only* will be emulated using i8 types.
 func.func @emulate_shrsi(%lhs : i16, %rhs : i16) -> (i16) {
   %res = arith.shrsi %lhs, %rhs : i16
   return %res : i16
 }
 

mlir/test/Integration/Dialect/Arith/CPU/test-wide-int-emulation-shrui-i16.mlir

 // Check that the wide integer `arith.shrui` emulation produces the same result as wide
 // `arith.shrui`. Emulate i16 ops with i8 ops.
 
 // RUN: mlir-opt %s --convert-scf-to-cf --convert-cf-to-llvm --convert-vector-to-llvm \
 // RUN:             --convert-func-to-llvm --convert-arith-to-llvm | \
 // RUN:   mlir-cpu-runner -e entry -entry-point-result=void \
-// RUN:                   --shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:                   --shared-libs=%mlir_c_runner_utils | \
 // RUN:   FileCheck %s --match-full-lines
 
 // RUN: mlir-opt %s --test-arith-emulate-wide-int="widest-int-supported=8" \
 // RUN:             --convert-scf-to-cf --convert-cf-to-llvm --convert-vector-to-llvm \
 // RUN:             --convert-func-to-llvm --convert-arith-to-llvm | \
 // RUN:   mlir-cpu-runner -e entry -entry-point-result=void \
-// RUN:                   --shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:                   --shared-libs=%mlir_c_runner_utils | \
 // RUN:   FileCheck %s --match-full-lines
 
 // Ops in this function *only* will be emulated using i8 types.
 func.func @emulate_shrui(%lhs : i16, %rhs : i16) -> (i16) {
   %res = arith.shrui %lhs, %rhs : i16
   return %res : i16
 }
 

mlir/test/Integration/Dialect/Async/CPU/lit.local.cfg

 import sys
 
-# No JIT on win32.
+# Windows does not have aligned_alloc
 if sys.platform == 'win32':
     config.unsupported = True

mlir/test/Integration/Dialect/Async/CPU/microbench-linalg-async-parallel-for.mlir

 // RUN:   mlir-opt %s                                                          \
 // RUN:               -convert-linalg-to-parallel-loops                        \
 // RUN:               -async-parallel-for                                      \
 // RUN:               -async-to-async-runtime                                  \
 // RUN:               -async-runtime-ref-counting                              \
 // RUN:               -async-runtime-ref-counting-opt                          \
 // RUN:               -convert-async-to-llvm                                   \
 // RUN:               -convert-scf-to-cf                                      \
 // RUN:               -arith-expand                                            \
 // RUN:               -memref-expand                                              \
 // RUN:               -convert-vector-to-llvm                                  \
 // RUN:               -finalize-memref-to-llvm                                  \
 // RUN:               -convert-func-to-llvm                                     \
 // RUN:               -reconcile-unrealized-casts                              \
 // RUN: | mlir-cpu-runner                                                      \
 // RUN: -e entry -entry-point-result=void -O3                                  \
-// RUN: -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext  \
-// RUN: -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext\
-// RUN: -shared-libs=%mlir_lib_dir/libmlir_async_runtime%shlibext \
+// RUN: -shared-libs=%mlir_runner_utils  \
+// RUN: -shared-libs=%mlir_c_runner_utils\
+// RUN: -shared-libs=%mlir_async_runtime \
 // RUN: | FileCheck %s --dump-input=always
 
 // RUN:   mlir-opt %s                                                          \
 // RUN:               -convert-linalg-to-loops                                 \
 // RUN:               -convert-scf-to-cf                                      \
 // RUN:               -convert-vector-to-llvm                                  \
 // RUN:               -finalize-memref-to-llvm                                  \
 // RUN:               -convert-func-to-llvm                                     \
 // RUN:               -reconcile-unrealized-casts                              \
 // RUN: | mlir-cpu-runner                                                      \
 // RUN: -e entry -entry-point-result=void -O3                                  \
-// RUN: -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext  \
-// RUN: -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext\
-// RUN: -shared-libs=%mlir_lib_dir/libmlir_async_runtime%shlibext \
+// RUN: -shared-libs=%mlir_runner_utils  \
+// RUN: -shared-libs=%mlir_c_runner_utils\
+// RUN: -shared-libs=%mlir_async_runtime \
 // RUN: | FileCheck %s --dump-input=always
 
 #map0 = affine_map<(d0, d1) -> (d0, d1)>
 
 func.func @linalg_generic(%lhs: memref<?x?xf32>,
                      %rhs: memref<?x?xf32>,
                      %sum: memref<?x?xf32>) {
   linalg.generic {

mlir/test/Integration/Dialect/Async/CPU/microbench-scf-async-parallel-for.mlir

 // RUN:   mlir-opt %s                                                          \
 // RUN:               -async-parallel-for                                      \
 // RUN:               -async-to-async-runtime                                  \
 // RUN:               -async-runtime-ref-counting                              \
 // RUN:               -async-runtime-ref-counting-opt                          \
 // RUN:               -convert-async-to-llvm                                   \
 // RUN:               -convert-linalg-to-loops                                 \
 // RUN:               -convert-scf-to-cf                                      \
 // RUN:               -arith-expand                                            \
 // RUN:               -memref-expand                                              \
 // RUN:               -convert-vector-to-llvm                                  \
 // RUN:               -finalize-memref-to-llvm                                  \
 // RUN:               -convert-func-to-llvm                                     \
 // RUN:               -reconcile-unrealized-casts                              \
 // RUN: | mlir-cpu-runner                                                      \
 // RUN: -e entry -entry-point-result=void -O3                                  \
-// RUN: -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext  \
-// RUN: -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext\
-// RUN: -shared-libs=%mlir_lib_dir/libmlir_async_runtime%shlibext \
+// RUN: -shared-libs=%mlir_runner_utils  \
+// RUN: -shared-libs=%mlir_c_runner_utils\
+// RUN: -shared-libs=%mlir_async_runtime \
 // RUN: | FileCheck %s --dump-input=always
 
 // RUN:   mlir-opt %s                                                          \
 // RUN:               -async-parallel-for=async-dispatch=false                 \
 // RUN:               -async-to-async-runtime                                  \
 // RUN:               -async-runtime-ref-counting                              \
 // RUN:               -async-runtime-ref-counting-opt                          \
 // RUN:               -convert-async-to-llvm                                   \
 // RUN:               -convert-linalg-to-loops                                 \
 // RUN:               -convert-scf-to-cf                                      \
 // RUN:               -arith-expand                                            \
 // RUN:               -memref-expand                                              \
 // RUN:               -convert-vector-to-llvm                                  \
 // RUN:               -finalize-memref-to-llvm                                  \
 // RUN:               -convert-func-to-llvm                                     \
 // RUN:               -reconcile-unrealized-casts                              \
 // RUN: | mlir-cpu-runner                                                      \
 // RUN: -e entry -entry-point-result=void -O3                                  \
-// RUN: -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext  \
-// RUN: -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext\
-// RUN: -shared-libs=%mlir_lib_dir/libmlir_async_runtime%shlibext \
+// RUN: -shared-libs=%mlir_runner_utils  \
+// RUN: -shared-libs=%mlir_c_runner_utils\
+// RUN: -shared-libs=%mlir_async_runtime \
 // RUN: | FileCheck %s --dump-input=always
 
 // RUN:   mlir-opt %s                                                          \
 // RUN:               -convert-linalg-to-loops                                 \
 // RUN:               -convert-scf-to-cf                                      \
 // RUN:               -convert-vector-to-llvm                                  \
 // RUN:               -finalize-memref-to-llvm                                  \
 // RUN:               -convert-func-to-llvm                                     \
 // RUN:               -reconcile-unrealized-casts                              \
 // RUN: | mlir-cpu-runner                                                      \
 // RUN: -e entry -entry-point-result=void -O3                                  \
-// RUN: -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext  \
-// RUN: -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext\
-// RUN: -shared-libs=%mlir_lib_dir/libmlir_async_runtime%shlibext \
+// RUN: -shared-libs=%mlir_runner_utils  \
+// RUN: -shared-libs=%mlir_c_runner_utils\
+// RUN: -shared-libs=%mlir_async_runtime \
 // RUN: | FileCheck %s --dump-input=always
 
 #map0 = affine_map<(d0, d1) -> (d0, d1)>
 
 func.func @scf_parallel(%lhs: memref<?x?xf32>,
                    %rhs: memref<?x?xf32>,
                    %sum: memref<?x?xf32>) {
   %c0 = arith.constant 0 : index

mlir/test/Integration/Dialect/Async/CPU/test-async-parallel-for-1d.mlir

 // RUN:   mlir-opt %s -async-parallel-for                                      \
 // RUN:               -async-to-async-runtime                                  \
 // RUN:               -async-runtime-ref-counting                              \
 // RUN:               -async-runtime-ref-counting-opt                          \
 // RUN:               -convert-async-to-llvm                                   \
 // RUN:               -convert-scf-to-cf                                      \
 // RUN:               -finalize-memref-to-llvm                                  \
 // RUN:               -arith-expand                                            \
 // RUN:               -memref-expand                                              \
 // RUN:               -convert-func-to-llvm                                     \
 // RUN:               -reconcile-unrealized-casts                              \
 // RUN: | mlir-cpu-runner                                                      \
 // RUN:  -e entry -entry-point-result=void -O0                                 \
-// RUN:  -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext \
-// RUN:  -shared-libs=%mlir_lib_dir/libmlir_async_runtime%shlibext\
+// RUN:  -shared-libs=%mlir_runner_utils \
+// RUN:  -shared-libs=%mlir_async_runtime\
 // RUN: | FileCheck %s --dump-input=always
 
 // RUN:   mlir-opt %s -async-parallel-for                                      \
 // RUN:               -async-to-async-runtime                                  \
 // RUN:               -async-runtime-policy-based-ref-counting                 \
 // RUN:               -convert-async-to-llvm                                   \
 // RUN:               -convert-scf-to-cf                                      \
 // RUN:               -finalize-memref-to-llvm                                  \
 // RUN:               -arith-expand                                            \
 // RUN:               -memref-expand                                              \
 // RUN:               -convert-func-to-llvm                                     \
 // RUN:               -reconcile-unrealized-casts                              \
 // RUN: | mlir-cpu-runner                                                      \
 // RUN:  -e entry -entry-point-result=void -O0                                 \
-// RUN:  -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext \
-// RUN:  -shared-libs=%mlir_lib_dir/libmlir_async_runtime%shlibext\
+// RUN:  -shared-libs=%mlir_runner_utils \
+// RUN:  -shared-libs=%mlir_async_runtime\
 // RUN: | FileCheck %s --dump-input=always
 
 // RUN:   mlir-opt %s -async-parallel-for="async-dispatch=false                \
 // RUN:                                    num-workers=20                      \
 // RUN:                                    min-task-size=1"                    \
 // RUN:               -async-to-async-runtime                                  \
 // RUN:               -async-runtime-ref-counting                              \
 // RUN:               -async-runtime-ref-counting-opt                          \
 // RUN:               -convert-async-to-llvm                                   \
 // RUN:               -convert-scf-to-cf                                      \
 // RUN:               -finalize-memref-to-llvm                                  \
 // RUN:               -arith-expand                                            \
 // RUN:               -memref-expand                                              \
 // RUN:               -convert-func-to-llvm                                     \
 // RUN:               -reconcile-unrealized-casts                              \
 // RUN: | mlir-cpu-runner                                                      \
 // RUN:  -e entry -entry-point-result=void -O0                                 \
-// RUN:  -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext \
-// RUN:  -shared-libs=%mlir_lib_dir/libmlir_async_runtime%shlibext\
+// RUN:  -shared-libs=%mlir_runner_utils \
+// RUN:  -shared-libs=%mlir_async_runtime\
 // RUN: | FileCheck %s --dump-input=always
 
 // Suppress constant folding by introducing "dynamic" zero value at runtime.
 func.func private @zero() -> index {
   %0 = arith.constant 0 : index
   return %0 : index
 }
 

mlir/test/Integration/Dialect/Async/CPU/test-async-parallel-for-2d.mlir

 // RUN:   mlir-opt %s -async-parallel-for                                      \
 // RUN:               -async-to-async-runtime                                  \
 // RUN:               -async-runtime-ref-counting                              \
 // RUN:               -async-runtime-ref-counting-opt                          \
 // RUN:               -arith-expand                                            \
 // RUN:               -convert-async-to-llvm                                   \
 // RUN:               -convert-scf-to-cf                                      \
 // RUN:               -finalize-memref-to-llvm                                  \
 // RUN:               -convert-func-to-llvm                                     \
 // RUN:               -reconcile-unrealized-casts                              \
 // RUN: | mlir-cpu-runner                                                      \
 // RUN:  -e entry -entry-point-result=void -O0                                 \
-// RUN:  -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext \
-// RUN:  -shared-libs=%mlir_lib_dir/libmlir_async_runtime%shlibext\
+// RUN:  -shared-libs=%mlir_runner_utils \
+// RUN:  -shared-libs=%mlir_async_runtime\
 // RUN: | FileCheck %s --dump-input=always
 
 // RUN:   mlir-opt %s -async-parallel-for                                      \
 // RUN:               -async-to-async-runtime                                  \
 // RUN:               -async-runtime-policy-based-ref-counting                 \
 // RUN:               -arith-expand                                            \
 // RUN:               -convert-async-to-llvm                                   \
 // RUN:               -convert-scf-to-cf                                      \
 // RUN:               -finalize-memref-to-llvm                                  \
 // RUN:               -convert-func-to-llvm                                     \
 // RUN:               -reconcile-unrealized-casts                              \
 // RUN: | mlir-cpu-runner                                                      \
 // RUN:  -e entry -entry-point-result=void -O0                                 \
-// RUN:  -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext \
-// RUN:  -shared-libs=%mlir_lib_dir/libmlir_async_runtime%shlibext\
+// RUN:  -shared-libs=%mlir_runner_utils \
+// RUN:  -shared-libs=%mlir_async_runtime\
 // RUN: | FileCheck %s --dump-input=always
 
 // RUN:   mlir-opt %s -async-parallel-for="async-dispatch=false                \
 // RUN:                                    num-workers=20                      \
 // RUN:                                    min-task-size=1"                    \
 // RUN:               -async-to-async-runtime                                  \
 // RUN:               -async-runtime-ref-counting                              \
 // RUN:               -async-runtime-ref-counting-opt                          \
 // RUN:               -arith-expand                                            \
 // RUN:               -convert-async-to-llvm                                   \
 // RUN:               -convert-scf-to-cf                                      \
 // RUN:               -finalize-memref-to-llvm                                  \
 // RUN:               -convert-func-to-llvm                                     \
 // RUN:               -reconcile-unrealized-casts                              \
 // RUN: | mlir-cpu-runner                                                      \
 // RUN:  -e entry -entry-point-result=void -O0                                 \
-// RUN:  -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext \
-// RUN:  -shared-libs=%mlir_lib_dir/libmlir_async_runtime%shlibext\
+// RUN:  -shared-libs=%mlir_runner_utils \
+// RUN:  -shared-libs=%mlir_async_runtime\
 // RUN: | FileCheck %s --dump-input=always
 
 func.func @entry() {
   %c0 = arith.constant 0.0 : f32
   %c1 = arith.constant 1 : index
   %c2 = arith.constant 2 : index
   %c8 = arith.constant 8 : index
 

mlir/test/Integration/Dialect/Complex/CPU/correctness.mlir

 // RUN: mlir-opt %s \
 // RUN:   -func-bufferize -tensor-bufferize -arith-bufferize --canonicalize \
 // RUN:   -convert-scf-to-cf --convert-complex-to-standard \
 // RUN:   -finalize-memref-to-llvm -convert-math-to-llvm -convert-math-to-libm \
 // RUN:   -convert-vector-to-llvm -convert-complex-to-llvm \
 // RUN:   -convert-func-to-llvm -reconcile-unrealized-casts |\
 // RUN: mlir-cpu-runner \
 // RUN:  -e entry -entry-point-result=void  \
-// RUN:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext |\
+// RUN:  -shared-libs=%mlir_c_runner_utils |\
 // RUN: FileCheck %s
 
 // XFAIL: target=aarch64{{.*}}
 // See: https://github.com/llvm/llvm-project/issues/58531
 
 func.func @test_unary(%input: tensor<?xcomplex<f32>>,
                       %func: (complex<f32>) -> complex<f32>) {
   %c0 = arith.constant 0 : index

mlir/test/Integration/Dialect/LLVMIR/CPU/X86/lit.local.cfg

 import platform
 
 if platform.machine() != 'x86_64':
     config.unsupported = True
-
-# No JIT on win32.
-if sys.platform == 'win32':
-    config.unsupported = True

mlir/test/Integration/Dialect/LLVMIR/CPU/X86/test-inline-asm-vector.mlir

 // RUN: mlir-opt %s -convert-vector-to-llvm |  \
 // RUN: mlir-cpu-runner -e entry_point_with_all_constants -entry-point-result=void \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext
+// RUN:   -shared-libs=%mlir_c_runner_utils
 
 module {
   llvm.func @function_to_run(%a: vector<8xf32>, %b: vector<8xf32>)  {
     // CHECK: ( 8, 10, 12, 14, 16, 18, 20, 22 )
     %r0 = llvm.inline_asm asm_dialect = intel
         "vaddps $0, $1, $2", "=x,x,x" %a, %b:
       (vector<8xf32>, vector<8xf32>) -> vector<8xf32>
     vector.print %r0: vector<8xf32>

mlir/test/Integration/Dialect/LLVMIR/CPU/X86/test-inline-asm.mlir

 // RUN: mlir-cpu-runner %s -e entry -entry-point-result=void  \
-// RUN: -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN: -shared-libs=%mlir_c_runner_utils | \
 // RUN: FileCheck %s
 
 module {
   llvm.func @printI64(i64)
   llvm.func @entry()  {
     %c2 = llvm.mlir.constant(-42: i64) :i64
     %val = llvm.inline_asm "xor $0, $0", "=r,r" %c2 :
       (i64) -> i64
 
     // CHECK: 0
     llvm.call @printI64(%val) : (i64) -> ()
     llvm.return
   }
 }

mlir/test/Integration/Dialect/LLVMIR/CPU/lit.local.cfg

 import sys
 
-# No JIT on win32.
-if sys.platform == 'win32':
-    config.unsupported = True
-
 lli_cmd = 'lli'
 if config.riscv_emulator_lli_executable:
     lli_cmd = config.riscv_emulator_lli_executable
 
 config.substitutions.append(('%mlir_native_utils_lib_dir',
     config.riscv_emulator_utils_lib_dir or config.mlir_lib_dir))
 
 if config.riscv_vector_emulator_executable:
     # Run test in qemu emulator.
     emulation_cmd = config.riscv_vector_emulator_executable
     if config.riscv_vector_emulator_options:
         emulation_cmd = emulation_cmd + ' ' + config.riscv_vector_emulator_options
     emulation_cmd = emulation_cmd + ' ' + lli_cmd + ' --march=riscv64 -mattr=+v '
     config.substitutions.append(('%lli', emulation_cmd))
 else:
     config.substitutions.append(('%lli', lli_cmd))

mlir/test/Integration/Dialect/LLVMIR/CPU/test-vector-reductions-fp.mlir

 // RUN: mlir-cpu-runner %s -e entry -entry-point-result=void  \
-// RUN: -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN: -shared-libs=%mlir_c_runner_utils | \
 // RUN: FileCheck %s
 
 // End-to-end test of all fp reduction intrinsics (not exhaustive unit tests).
 module {
   llvm.func @printNewline()
   llvm.func @printF32(f32)
   llvm.func @entry() {
     // Setup (1,2,3,4).

mlir/test/Integration/Dialect/LLVMIR/CPU/test-vector-reductions-int.mlir

 // RUN: mlir-cpu-runner %s -e entry -entry-point-result=void  \
-// RUN: -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN: -shared-libs=%mlir_c_runner_utils | \
 // RUN: FileCheck %s
 
 // End-to-end test of all int reduction intrinsics (not exhaustive unit tests).
 module {
   llvm.func @printNewline()
   llvm.func @printI64(i64)
   llvm.func @entry() {
     // Setup (1,2,3,4).

mlir/test/Integration/Dialect/LLVMIR/CPU/test-vp-intrinsic.mlir

 // RUN: mlir-opt %s -convert-vector-to-llvm -finalize-memref-to-llvm \
 // RUN:             -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-translate -mlir-to-llvmir | \
 // RUN: %lli --entry-function=entry \
 // RUN:      --dlopen=%mlir_native_utils_lib_dir/libmlir_c_runner_utils%shlibext | \
 // RUN: FileCheck %s
 
+// %mlir_native_utils_lib_dir is incorrect on Windows
+// UNSUPPORTED: system-windows
+
 memref.global "private" @gv_i32 : memref<20xi32> =
     dense<[0, 1, 2, 3, 4, 5, 6, 7, 8, 9,
            10, 11, 12, 13, 14, 15, 16, 17, 18, 19]>
 
 func.func @entry() -> i32 {
   %c0 = arith.constant 0 : index
   %c10 = arith.constant 10 : index
   %mem_i32 = memref.get_global @gv_i32 : memref<20xi32>

mlir/test/Integration/Dialect/Linalg/CPU/matmul-vs-matvec.mlir

 // RUN: mlir-opt %s -convert-linalg-to-loops -convert-scf-to-cf -convert-linalg-to-llvm -expand-strided-metadata -lower-affine -convert-arith-to-llvm -finalize-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -O3 -e main -entry-point-result=void \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext \
+// RUN:   -shared-libs=%mlir_runner_utils \
 // RUN: | FileCheck %s
 
 func.func private @printMemrefF32(memref<*xf32>)
 
 func.func @matmul(%A: memref<?x?xf32>, %B: memref<?x?xf32>) -> (memref<?x?xf32>) {
   %c0 = arith.constant 0 : index
   %c1 = arith.constant 1 : index
   %f0 = arith.constant 0.0 : f32

mlir/test/Integration/Dialect/Linalg/CPU/rank-reducing-subview.mlir

 // RUN: mlir-opt %s -convert-linalg-to-loops -convert-scf-to-cf -convert-linalg-to-llvm -expand-strided-metadata -lower-affine -convert-arith-to-llvm -finalize-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -O3 -e main -entry-point-result=void \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext \
+// RUN:   -shared-libs=%mlir_runner_utils \
 // RUN: | FileCheck %s
 
 func.func private @printMemrefF32(memref<*xf32>)
 
 func.func @main() {
   %c0 = arith.constant 0 : index
   %c1 = arith.constant 1 : index
   %c2 = arith.constant 2 : index

mlir/test/Integration/Dialect/Linalg/CPU/test-collapse-tensor.mlir

 // RUN: mlir-opt %s -linalg-bufferize \
 // RUN: -arith-bufferize -tensor-bufferize -func-bufferize \
 // RUN: -finalizing-bufferize -buffer-deallocation -convert-linalg-to-llvm \
 // RUN: -expand-strided-metadata -lower-affine \
 // RUN: -finalize-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e main -entry-point-result=void \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext \
+// RUN:   -shared-libs=%mlir_runner_utils \
 // RUN: | FileCheck %s
 
 
 func.func @main() {
   %const = arith.constant dense<[[[[-3.9058,0.9072],[-2.9470,-2.2055],[18.3946,8.2997]],[[3.4700,5.9006],[-17.2267,4.9777],[1.0450,-0.8201]]],[[[17.6996,-11.1763],[26.7775,-3.8823],[-4.2492,-5.8966]],[[2.1259,13.1794],[-10.7136,0.8428],[16.4233,9.4589]]]]> : tensor<2x2x3x2xf32>
   %dynamic = tensor.cast %const: tensor<2x2x3x2xf32> to tensor<2x?x?x?xf32>
   %collapsed = call @collapse_dynamic_shape(%dynamic) : (tensor<2x?x?x?xf32>) -> (tensor<2x?x?xf32>)
   %unranked = tensor.cast %collapsed: tensor<2x?x?xf32> to tensor<*xf32>

mlir/test/Integration/Dialect/Linalg/CPU/test-conv-1d-call.mlir

 // RUN: mlir-opt %s -test-transform-dialect-erase-schedule -convert-linalg-to-loops -convert-scf-to-cf -convert-linalg-to-llvm -expand-strided-metadata -lower-affine -convert-arith-to-llvm -convert-scf-to-cf --finalize-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e main -entry-point-result=void \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext \
+// RUN:   -shared-libs=%mlir_runner_utils \
 // RUN: | FileCheck %s
 
 // RUN: mlir-opt %s -test-transform-dialect-interpreter -test-transform-dialect-erase-schedule -convert-linalg-to-loops -convert-scf-to-cf \
 // RUN:   -convert-linalg-to-llvm -expand-strided-metadata -lower-affine -convert-arith-to-llvm -convert-scf-to-cf --finalize-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e main -entry-point-result=void \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext \
+// RUN:   -shared-libs=%mlir_runner_utils \
 // RUN: | FileCheck %s
 
 func.func private @printMemrefF32(memref<*xf32>)
 
 // Creates and returns a 1-D buffer of size %s1 filled with the value %f
 func.func @alloc_1d_filled_f32(%s1 : index, %f : f32) -> memref<?xf32> {
   %buf = memref.alloc(%s1) : memref<?xf32>
   linalg.fill ins(%f : f32) outs(%buf : memref<?xf32>)

mlir/test/Integration/Dialect/Linalg/CPU/test-conv-1d-nwc-wcf-call.mlir

 // RUN: mlir-opt %s -test-transform-dialect-erase-schedule -convert-linalg-to-loops -convert-scf-to-cf -convert-linalg-to-llvm -expand-strided-metadata -lower-affine -convert-arith-to-llvm -convert-scf-to-cf --finalize-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e main -entry-point-result=void \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext \
+// RUN:   -shared-libs=%mlir_runner_utils \
 // RUN: | FileCheck %s
 
 // RUN: mlir-opt %s -test-transform-dialect-interpreter -test-transform-dialect-erase-schedule -convert-linalg-to-loops -convert-scf-to-cf \
 // RUN:   -convert-linalg-to-llvm -expand-strided-metadata -lower-affine -convert-arith-to-llvm -convert-scf-to-cf --finalize-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e main -entry-point-result=void \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext \
+// RUN:   -shared-libs=%mlir_runner_utils \
 // RUN: | FileCheck %s
 
 func.func private @printMemrefF32(memref<*xf32>)
 
 // Creates and returns 3-D buffer of size (%s1, %s2, %s3) filled with the value %f
 func.func @alloc_3d_filled_f32(%s1 : index, %s2 : index, %s3 : index, %f : f32) -> memref<?x?x?xf32> {
   %buf = memref.alloc(%s1, %s2, %s3) : memref<?x?x?xf32>
   linalg.fill ins(%f : f32) outs(%buf : memref<?x?x?xf32>)

mlir/test/Integration/Dialect/Linalg/CPU/test-conv-2d-call.mlir

 // RUN: mlir-opt %s -test-transform-dialect-erase-schedule -convert-linalg-to-loops -convert-scf-to-cf -convert-linalg-to-llvm -expand-strided-metadata -lower-affine -convert-arith-to-llvm -convert-scf-to-cf --finalize-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e main -entry-point-result=void \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext \
+// RUN:   -shared-libs=%mlir_runner_utils \
 // RUN: | FileCheck %s
 
 // RUN: mlir-opt %s -test-transform-dialect-interpreter -test-transform-dialect-erase-schedule -convert-linalg-to-loops -convert-scf-to-cf \
 // RUN:   -convert-linalg-to-llvm -expand-strided-metadata -lower-affine -convert-arith-to-llvm -convert-scf-to-cf --finalize-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e main -entry-point-result=void \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext \
+// RUN:   -shared-libs=%mlir_runner_utils \
 // RUN: | FileCheck %s
 
 func.func private @printMemrefF32(memref<*xf32>)
 
 // Creates and returns a 2-D buffer of size (%s1, %s2) filled with the value %f
 func.func @alloc_2d_filled_f32(%s1 : index, %s2 : index, %f : f32) -> memref<?x?xf32> {
   %buf = memref.alloc(%s1, %s2) : memref<?x?xf32>
   linalg.fill ins(%f : f32) outs(%buf : memref<?x?xf32>)

mlir/test/Integration/Dialect/Linalg/CPU/test-conv-2d-nhwc-hwcf-call.mlir

 // RUN: mlir-opt %s -test-transform-dialect-erase-schedule -convert-linalg-to-loops -convert-scf-to-cf -convert-linalg-to-llvm -expand-strided-metadata -lower-affine -convert-arith-to-llvm -convert-scf-to-cf --finalize-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e main -entry-point-result=void \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext \
+// RUN:   -shared-libs=%mlir_runner_utils \
 // RUN: | FileCheck %s
 
 // RUN: mlir-opt %s -test-transform-dialect-interpreter -test-transform-dialect-erase-schedule -convert-linalg-to-loops -convert-scf-to-cf \
 // RUN:   -convert-linalg-to-llvm -expand-strided-metadata -lower-affine -convert-arith-to-llvm -convert-scf-to-cf --finalize-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e main -entry-point-result=void \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext \
+// RUN:   -shared-libs=%mlir_runner_utils \
 // RUN: | FileCheck %s
 
 func.func private @printMemrefF32(memref<*xf32>)
 
 // Creates and returns 4-D buffer of size (%s1, %s2, %s3, %s4) filled with the value %f
 func.func @alloc_4d_filled_f32(%s1 : index, %s2 : index, %s3 : index, %s4 : index, %f : f32) -> memref<?x?x?x?xf32> {
   %buf = memref.alloc(%s1, %s2, %s3, %s4) : memref<?x?x?x?xf32>
   linalg.fill ins(%f : f32) outs(%buf : memref<?x?x?x?xf32>)

mlir/test/Integration/Dialect/Linalg/CPU/test-conv-3d-call.mlir

 // RUN: mlir-opt %s -test-transform-dialect-erase-schedule -convert-linalg-to-loops -convert-scf-to-cf -convert-linalg-to-llvm -expand-strided-metadata -lower-affine -convert-arith-to-llvm -convert-scf-to-cf --finalize-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e main -entry-point-result=void \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext \
+// RUN:   -shared-libs=%mlir_runner_utils \
 // RUN: | FileCheck %s
 
 // RUN: mlir-opt %s -test-transform-dialect-interpreter -test-transform-dialect-erase-schedule -convert-linalg-to-loops -convert-scf-to-cf \
 // RUN:   -convert-linalg-to-llvm -expand-strided-metadata -lower-affine -convert-arith-to-llvm -convert-scf-to-cf --finalize-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e main -entry-point-result=void \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext \
+// RUN:   -shared-libs=%mlir_runner_utils \
 // RUN: | FileCheck %s
 
 func.func private @printMemrefF32(memref<*xf32>)
 
 // Creates and returns 3-D buffer of size (%s1, %s2, %s3) filled with the value %f
 func.func @alloc_3d_filled_f32(%s1 : index, %s2 : index, %s3 : index, %f : f32) -> memref<?x?x?xf32> {
   %buf = memref.alloc(%s1, %s2, %s3) : memref<?x?x?xf32>
   linalg.fill ins(%f : f32) outs(%buf : memref<?x?x?xf32>)

mlir/test/Integration/Dialect/Linalg/CPU/test-conv-3d-ndhwc-dhwcf-call.mlir

 // RUN: mlir-opt %s -test-transform-dialect-erase-schedule -convert-linalg-to-loops -convert-scf-to-cf -convert-linalg-to-llvm -expand-strided-metadata -lower-affine -convert-arith-to-llvm -convert-scf-to-cf --finalize-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e main -entry-point-result=void \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext \
+// RUN:   -shared-libs=%mlir_runner_utils \
 // RUN: | FileCheck %s
 
 // RUN: mlir-opt %s -test-transform-dialect-interpreter -test-transform-dialect-erase-schedule -convert-linalg-to-loops -convert-scf-to-cf \
 // RUN:   -convert-linalg-to-llvm -expand-strided-metadata -lower-affine -convert-arith-to-llvm -convert-scf-to-cf --finalize-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e main -entry-point-result=void \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext \
+// RUN:   -shared-libs=%mlir_runner_utils \
 // RUN: | FileCheck %s
 
 func.func private @printMemrefF32(memref<*xf32>)
 
 // Creates and returns 5-D buffer of size (%s1, %s2, %s3, %s4, %s5) filled with the value %f
 func.func @alloc_5d_filled_f32(%s1 : index, %s2 : index, %s3 : index, %s4 : index, %s5 : index, %f : f32) -> memref<?x?x?x?x?xf32> {
   %buf = memref.alloc(%s1, %s2, %s3, %s4, %s5) : memref<?x?x?x?x?xf32>
   linalg.fill ins(%f : f32) outs(%buf : memref<?x?x?x?x?xf32>)

mlir/test/Integration/Dialect/Linalg/CPU/test-elementwise.mlir

 // RUN: mlir-opt %s -convert-elementwise-to-linalg \
 // RUN: -arith-bufferize -linalg-bufferize -tensor-bufferize \
 // RUN: -func-bufferize -buffer-deallocation -convert-linalg-to-loops \
 // RUN: -convert-linalg-to-llvm --finalize-memref-to-llvm -convert-func-to-llvm \
 // RUN: -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e main -entry-point-result=void \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext \
+// RUN:   -shared-libs=%mlir_runner_utils \
 // RUN: | FileCheck %s
 
 func.func @main() {
   %a = arith.constant dense<[1.0, 2.0, 3.0]> : tensor<3xf32>
   %b = arith.constant dense<[10.0, 20.0, 30.0]> : tensor<3xf32>
 
   %addf = arith.addf %a, %b : tensor<3xf32>
   %addf_unranked = tensor.cast %addf : tensor<3xf32> to tensor<*xf32>
   call @printMemrefF32(%addf_unranked) : (tensor<*xf32>) -> ()
   // CHECK: Unranked Memref base@ = {{.*}} rank = 1 offset = 0 sizes = [3] strides = [1] data =
   // CHECK-NEXT: [11,  22,  33]
 
   return
 }
 
 func.func private @printMemrefF32(%ptr : tensor<*xf32>)

mlir/test/Integration/Dialect/Linalg/CPU/test-expand-tensor.mlir

 // RUN: mlir-opt %s -linalg-bufferize \
 // RUN: -arith-bufferize -tensor-bufferize -func-bufferize \
 // RUN: -finalizing-bufferize -buffer-deallocation -convert-linalg-to-llvm \
 // RUN: -expand-strided-metadata -lower-affine \
 // RUN: -finalize-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e main -entry-point-result=void \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext \
+// RUN:   -shared-libs=%mlir_runner_utils \
 // RUN: | FileCheck %s
 
 
 func.func @main() {
   %const = arith.constant dense<[[[-3.9058,0.9072],[-2.9470,-2.2055],[18.3946,8.2997],[3.4700,5.9006],[-17.2267,4.9777],[1.0450,-0.8201]],[[17.6996,-11.1763],[26.7775,-3.8823],[-4.2492,-5.8966],[2.1259,13.1794],[-10.7136,0.8428],[16.4233,9.4589]]]> : tensor<2x6x2xf32>
   %dynamic = tensor.cast %const: tensor<2x6x2xf32> to tensor<2x?x?xf32>
   %expanded = call @expand_dynamic_shape(%dynamic) : (tensor<2x?x?xf32>) -> (tensor<2x2x?x1x?xf32>)
   %unranked = tensor.cast %expanded: tensor<2x2x?x1x?xf32> to tensor<*xf32>

mlir/test/Integration/Dialect/Linalg/CPU/test-one-shot-bufferize.mlir

 // RUN: mlir-opt %s -pass-pipeline="builtin.module(func.func(canonicalize,cse),one-shot-bufferize{bufferize-function-boundaries})" |\
 // RUN: mlir-opt -pass-pipeline="builtin.module(func.func(buffer-deallocation,convert-vector-to-scf,lower-affine,convert-linalg-to-loops))" |\
 // RUN: mlir-opt -pass-pipeline="builtin.module(func.func(canonicalize,convert-scf-to-cf),convert-vector-to-llvm,expand-strided-metadata,lower-affine,convert-arith-to-llvm,finalize-memref-to-llvm,convert-func-to-llvm,reconcile-unrealized-casts)" | \
 
 // RUN: mlir-cpu-runner -O3 -e main -entry-point-result=void \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext,%mlir_lib_dir/libmlir_c_runner_utils%shlibext |\
+// RUN:   -shared-libs=%mlir_runner_utils,%mlir_c_runner_utils |\
 // RUN: FileCheck %s
 
 #map0 = affine_map<(d0, d1)[s0] -> ((d1 - d0) ceildiv s0)>
 #map1 = affine_map<(d0, d1)[s0] -> ((d0 - d1) ceildiv s0)>
 
 func.func @init_and_dot(%arg0: tensor<64xf32>, %arg1: tensor<64xf32>, %arg2: tensor<f32>) -> tensor<f32> {
   %c64 = arith.constant 64 : index
   %cst = arith.constant 0.000000e+00 : f32

mlir/test/Integration/Dialect/Linalg/CPU/test-padtensor.mlir

 // RUN: mlir-opt %s -test-linalg-transform-patterns=test-linalg-to-vector-patterns \
 // RUN: -empty-tensor-to-alloc-tensor -linalg-bufferize -arith-bufferize \
 // RUN: -bufferization-bufferize -tensor-bufferize -func-bufferize \
 // RUN: -finalizing-bufferize -buffer-deallocation \
 // RUN: -convert-linalg-to-loops -convert-scf-to-cf -convert-linalg-to-llvm -expand-strided-metadata -lower-affine -convert-arith-to-llvm -finalize-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e main -entry-point-result=void \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext,%mlir_lib_dir/libmlir_runner_utils%shlibext \
+// RUN:   -shared-libs=%mlir_c_runner_utils,%mlir_runner_utils \
 // RUN: | FileCheck %s
 
 
 func.func @main() {
   %const = arith.constant dense<[[[1.0, 2.0, 3.0], [2.0, 3.0, 4.0]]]> : tensor<1x2x3xf32>
   %dynamic = tensor.cast %const: tensor<1x2x3xf32> to tensor<1x?x3xf32>
   %offset = arith.constant 2 : index
   %cst = arith.constant 2.3 : f32

mlir/test/Integration/Dialect/Linalg/CPU/test-subtensor-insert-multiple-uses.mlir

 // RUN: mlir-opt %s -linalg-bufferize \
 // RUN: -arith-bufferize -tensor-bufferize -func-bufferize \
 // RUN: -finalizing-bufferize -buffer-deallocation \
 // RUN: -convert-linalg-to-loops -convert-scf-to-cf -convert-linalg-to-llvm -expand-strided-metadata -lower-affine -convert-arith-to-llvm --finalize-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e main -entry-point-result=void \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext,%mlir_lib_dir/libmlir_runner_utils%shlibext \
+// RUN:   -shared-libs=%mlir_c_runner_utils,%mlir_runner_utils \
 // RUN: | FileCheck %s
 
 func.func @main() {
   %const = arith.constant dense<10.0> : tensor<2xf32>
   %insert_val = arith.constant dense<20.0> : tensor<1xf32>
 
   // Both of these insert_slice ops insert into the same original tensor
   // value `%const`. This can easily cause bugs if at the memref level

mlir/test/Integration/Dialect/Linalg/CPU/test-subtensor-insert.mlir

 // RUN: mlir-opt %s -linalg-bufferize \
 // RUN: -arith-bufferize -tensor-bufferize -func-bufferize \
 // RUN: -finalizing-bufferize -buffer-deallocation \
 // RUN: -convert-linalg-to-loops -convert-scf-to-cf -convert-linalg-to-llvm -expand-strided-metadata -lower-affine -convert-arith-to-llvm --finalize-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e main -entry-point-result=void \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext \
+// RUN:   -shared-libs=%mlir_runner_utils \
 // RUN: | FileCheck %s
 
 func.func @main() {
   %const = arith.constant dense<10.0> : tensor<2xf32>
   %insert_val = arith.constant dense<20.0> : tensor<1xf32>
   %inserted = tensor.insert_slice %insert_val into %const[0][1][1] : tensor<1xf32> into tensor<2xf32>
 
   %unranked = tensor.cast %inserted : tensor<2xf32> to tensor<*xf32>

mlir/test/Integration/Dialect/Linalg/CPU/test-tensor-e2e.mlir

 // RUN: mlir-opt %s -arith-bufferize -linalg-bufferize \
 // RUN: -tensor-bufferize -func-bufferize -finalizing-bufferize -buffer-deallocation -convert-linalg-to-loops \
 // RUN: -convert-linalg-to-llvm --finalize-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e main -entry-point-result=void \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext \
+// RUN:   -shared-libs=%mlir_runner_utils \
 // RUN: | FileCheck %s
 
 func.func @foo() -> tensor<4xf32> {
   %0 = arith.constant dense<[1.0, 2.0, 3.0, 4.0]> : tensor<4xf32>
   return %0 : tensor<4xf32>
 }
 
 func.func @main() {

mlir/test/Integration/Dialect/Linalg/CPU/test-tensor-matmul.mlir

 // UNSUPPORTED: asan
 // RUN: mlir-opt %s -test-transform-dialect-erase-schedule -linalg-bufferize -arith-bufferize \
 // RUN: -tensor-bufferize -func-bufferize -finalizing-bufferize -buffer-deallocation -convert-linalg-to-loops -convert-scf-to-cf \
 // RUN: -convert-linalg-to-llvm -expand-strided-metadata -lower-affine -convert-arith-to-llvm -convert-scf-to-cf --finalize-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e main -entry-point-result=void \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext,%mlir_lib_dir/libmlir_runner_utils%shlibext \
+// RUN:   -shared-libs=%mlir_c_runner_utils,%mlir_runner_utils \
 // RUN: | FileCheck %s
 
 // RUN: mlir-opt %s -test-transform-dialect-interpreter -test-transform-dialect-erase-schedule -linalg-bufferize \
 // RUN: -scf-bufferize -arith-bufferize -tensor-bufferize \
 // RUN: -func-bufferize \
 // RUN: -finalizing-bufferize -convert-linalg-to-loops -convert-scf-to-cf -convert-scf-to-cf \
 // RUN: -convert-linalg-to-llvm -expand-strided-metadata -lower-affine -convert-arith-to-llvm -convert-scf-to-cf --finalize-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e main -entry-point-result=void \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext,%mlir_lib_dir/libmlir_runner_utils%shlibext \
+// RUN:   -shared-libs=%mlir_c_runner_utils,%mlir_runner_utils \
 // RUN: | FileCheck %s
 
 func.func @main() {
   %A = arith.constant dense<[[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]]> : tensor<2x3xf32>
   %B = arith.constant dense<[[1.0, 2.0, 3.0, 4.0],
                        [5.0, 6.0, 7.0, 8.0],
                        [9.0, 10.0, 11.0, 12.0]]> : tensor<3x4xf32>
   %C = arith.constant dense<1000.0> : tensor<2x4xf32>

mlir/test/Integration/Dialect/Memref/cast-runtime-verification.mlir

 // RUN: mlir-opt %s -generate-runtime-verification -finalize-memref-to-llvm \
 // RUN:     -test-cf-assert \
 // RUN:     -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e main -entry-point-result=void \
-// RUN:     -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext 2>&1 | \
+// RUN:     -shared-libs=%mlir_runner_utils 2>&1 | \
 // RUN: FileCheck %s
 
 func.func @cast_to_static_dim(%m: memref<?xf32>) -> memref<10xf32> {
   %0 = memref.cast %m : memref<?xf32> to memref<10xf32>
   return %0 : memref<10xf32>
 }
 
 func.func @cast_to_ranked(%m: memref<*xf32>) -> memref<f32> {

mlir/test/Integration/Dialect/SparseTensor/CPU/concatenate.mlir

 // DEFINE: %{option} = enable-runtime-library=true
 // DEFINE: %{compile} = mlir-opt %s --sparse-compiler=%{option}
 // DEFINE: %{run} = mlir-cpu-runner \
 // DEFINE:  -e entry -entry-point-result=void  \
-// DEFINE:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext,%mlir_lib_dir/libmlir_runner_utils%shlibext | \
+// DEFINE:  -shared-libs=%mlir_c_runner_utils,%mlir_runner_utils | \
 // DEFINE: FileCheck %s
 //
 // RUN: %{compile} | %{run}
 //
 // Do the same run, but now with direct IR generation.
 // REDEFINE: %{option} = "enable-runtime-library=false enable-buffer-initialization=true"
 // RUN: %{compile} | %{run}
 //
 // Do the same run, but now with direct IR generation and vectorization.
 // REDEFINE: %{option} = "enable-runtime-library=false enable-buffer-initialization=true vl=2 reassociate-fp-reductions=true enable-index-optimizations=true"
 // RUN: %{compile} | %{run}
 
 // Do the same run, but now with direct IR generation and, if available, VLA
 // vectorization.
 // REDEFINE: %{option} = "enable-runtime-library=false vl=4 enable-arm-sve=%ENABLE_VLA"
 // REDEFINE: %{run} = %lli \
 // REDEFINE:   --entry-function=entry_lli \
 // REDEFINE:   --extra-module=%S/Inputs/main_for_lli.ll \
 // REDEFINE:   %VLA_ARCH_ATTR_OPTIONS \
-// REDEFINE:   --dlopen=%mlir_native_utils_lib_dir/libmlir_c_runner_utils%shlibext --dlopen=%mlir_lib_dir/libmlir_runner_utils%shlibext | \
+// REDEFINE:   --dlopen=%mlir_native_utils_lib_dir/libmlir_c_runner_utils%shlibext --dlopen=%mlir_runner_utils | \
 // REDEFINE: FileCheck %s
 // RUN: %{compile} | mlir-translate -mlir-to-llvmir | %{run}
 
 #MAT_C_C = #sparse_tensor.encoding<{dimLevelType = ["compressed", "compressed"]}>
 #MAT_D_C = #sparse_tensor.encoding<{dimLevelType = ["dense", "compressed"]}>
 #MAT_C_D = #sparse_tensor.encoding<{dimLevelType = ["compressed", "dense"]}>
 #MAT_D_D = #sparse_tensor.encoding<{
   dimLevelType = ["dense", "dense"],

mlir/test/Integration/Dialect/SparseTensor/CPU/dense_output.mlir

 // DEFINE: %{option} = enable-runtime-library=true
 // DEFINE: %{compile} = mlir-opt %s --sparse-compiler=%{option}
 // DEFINE: %{run} = TENSOR0="%mlir_src_dir/test/Integration/data/test.mtx" \
 // DEFINE: mlir-cpu-runner \
 // DEFINE:  -e entry -entry-point-result=void  \
-// DEFINE:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext,%mlir_lib_dir/libmlir_runner_utils%shlibext | \
+// DEFINE:  -shared-libs=%mlir_c_runner_utils,%mlir_runner_utils | \
 // DEFINE: FileCheck %s
 //
 // RUN: %{compile} | %{run}
 //
 // Do the same run, but now with direct IR generation.
 // REDEFINE: %{option} = enable-runtime-library=false
 // RUN: %{compile} | %{run}
 //
 // Do the same run, but now with direct IR generation and vectorization.
 // REDEFINE: %{option} = "enable-runtime-library=false vl=2 reassociate-fp-reductions=true enable-index-optimizations=true"
 // RUN: %{compile} | %{run}
 
 // Do the same run, but now with direct IR generation and, if available, VLA
 // vectorization.
 // REDEFINE: %{option} = "enable-runtime-library=false vl=4 enable-arm-sve=%ENABLE_VLA"
 // REDEFINE: %{run} = TENSOR0="%mlir_src_dir/test/Integration/data/test.mtx" \
 // REDEFINE: %lli \
 // REDEFINE:   --entry-function=entry_lli \
 // REDEFINE:   --extra-module=%S/Inputs/main_for_lli.ll \
 // REDEFINE:   %VLA_ARCH_ATTR_OPTIONS \
-// REDEFINE:   --dlopen=%mlir_native_utils_lib_dir/libmlir_c_runner_utils%shlibext --dlopen=%mlir_lib_dir/libmlir_runner_utils%shlibext | \
+// REDEFINE:   --dlopen=%mlir_native_utils_lib_dir/libmlir_c_runner_utils%shlibext --dlopen=%mlir_runner_utils | \
 // REDEFINE: FileCheck %s
 // RUN: %{compile} | mlir-translate -mlir-to-llvmir | %{run}
 
 !Filename = !llvm.ptr<i8>
 
 #DenseMatrix = #sparse_tensor.encoding<{
   dimLevelType = [ "dense", "dense" ],
   dimOrdering = affine_map<(i,j) -> (i,j)>

mlir/test/Integration/Dialect/SparseTensor/CPU/dense_output_bf16.mlir

 // DEFINE: %{option} = enable-runtime-library=true
 // DEFINE: %{command} = mlir-opt %s --sparse-compiler=%{option} | \
 // DEFINE: mlir-cpu-runner \
 // DEFINE:  -e entry -entry-point-result=void  \
-// DEFINE:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// DEFINE:  -shared-libs=%mlir_c_runner_utils | \
 // DEFINE: FileCheck %s
 //
 // RUN: %{command}
 //
 // Do the same run, but now with direct IR generation.
 // REDEFINE: %{option} = enable-runtime-library=false
 // RUN: %{command}
 //

mlir/test/Integration/Dialect/SparseTensor/CPU/dense_output_f16.mlir

 // DEFINE: %{option} = enable-runtime-library=true
 // DEFINE: %{compile} = mlir-opt %s --sparse-compiler=%{option}
 // DEFINE: %{run} = mlir-cpu-runner \
 // DEFINE:  -e entry -entry-point-result=void  \
-// DEFINE:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// DEFINE:  -shared-libs=%mlir_c_runner_utils | \
 // DEFINE: FileCheck %s
 //
 // RUN: %{compile} | %{run}
 //
 // Do the same run, but now with direct IR generation.
 // REDEFINE: %{option} = enable-runtime-library=false
 // RUN: %{compile} | %{run}
 //

mlir/test/Integration/Dialect/SparseTensor/CPU/lit.local.cfg

 import sys
 
-# No JIT on win32.
+# FIXME: %mlir_native_utils_lib_dir is set incorrectly on Windows
 if sys.platform == 'win32':
     config.unsupported = True
 
 # ArmSVE tests must be enabled via build flag.
 if config.mlir_run_arm_sve_tests:
     config.substitutions.append(('%ENABLE_VLA', 'true'))
     config.substitutions.append(('%VLA_ARCH_ATTR_OPTIONS', '--march=aarch64 --mattr="+sve"'))
     lli_cmd = 'lli'

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_abs.mlir

 // DEFINE: %{option} = enable-runtime-library=true
 // DEFINE: %{compile} = mlir-opt %s --sparse-compiler=%{option}
 // DEFINE: %{run} = mlir-cpu-runner \
 // DEFINE:  -e entry -entry-point-result=void  \
-// DEFINE:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// DEFINE:  -shared-libs=%mlir_c_runner_utils | \
 // DEFINE: FileCheck %s
 //
 // RUN: %{compile} | %{run}
 //
 // Do the same run, but now with direct IR generation.
 // REDEFINE: %{option} = enable-runtime-library=false
 // RUN: %{compile} | %{run}
 //

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_binary.mlir

 // DEFINE: %{option} = enable-runtime-library=true
 // DEFINE: %{compile} = mlir-opt %s --sparse-compiler=%{option}
 // DEFINE: %{run} = mlir-cpu-runner \
 // DEFINE:  -e entry -entry-point-result=void  \
-// DEFINE:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// DEFINE:  -shared-libs=%mlir_c_runner_utils | \
 // DEFINE: FileCheck %s
 //
 // RUN: %{compile} | %{run}
 //
 // Do the same run, but now with direct IR generation.
 // REDEFINE: %{option} = "enable-runtime-library=false enable-buffer-initialization=true"
 // RUN: %{compile} | %{run}
 //

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_cast.mlir

 // DEFINE: %{option} = enable-runtime-library=true
 // DEFINE: %{compile} = mlir-opt %s --sparse-compiler=%{option}
 // DEFINE: %{run} = mlir-cpu-runner \
 // DEFINE:  -e entry -entry-point-result=void  \
-// DEFINE:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// DEFINE:  -shared-libs=%mlir_c_runner_utils | \
 // DEFINE: FileCheck %s
 //
 // RUN: %{compile} | %{run}
 //
 // Do the same run, but now with direct IR generation.
 // REDEFINE: %{option} = enable-runtime-library=false
 // RUN: %{compile} | %{run}
 //

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_codegen_dim.mlir

 // DEFINE: %{option} = enable-runtime-library=true
 // DEFINE: %{compile} = mlir-opt %s --sparse-compiler=%{option}
 // DEFINE: %{run} = mlir-cpu-runner \
 // DEFINE:  -e entry -entry-point-result=void  \
-// DEFINE:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// DEFINE:  -shared-libs=%mlir_c_runner_utils | \
 // DEFINE: FileCheck %s
 //
 // RUN: %{compile} | %{run}
 //
 // Do the same run, but now with direct IR generation.
 // REDEFINE: %{option} = enable-runtime-library=false
 // RUN: %{compile} | %{run}
 //

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_codegen_foreach.mlir

 // DEFINE: %{option} = enable-runtime-library=true
 // DEFINE: %{compile} = mlir-opt %s --sparse-compiler=%{option}
 // DEFINE: %{run} = mlir-cpu-runner \
 // DEFINE:  -e entry -entry-point-result=void  \
-// DEFINE:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// DEFINE:  -shared-libs=%mlir_c_runner_utils | \
 // DEFINE: FileCheck %s
 //
 // RUN: %{compile} | %{run}
 //
 // Do the same run, but now with direct IR generation.
 // REDEFINE: %{option} = enable-runtime-library=false
 // RUN: %{compile} | %{run}
 //

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_complex32.mlir

 // DEFINE: %{option} = enable-runtime-library=true
 // DEFINE: %{compile} = mlir-opt %s --sparse-compiler=%{option}
 // DEFINE: %{run} = mlir-cpu-runner \
 // DEFINE:  -e entry -entry-point-result=void  \
-// DEFINE:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// DEFINE:  -shared-libs=%mlir_c_runner_utils | \
 // DEFINE: FileCheck %s
 //
 // RUN: %{compile} | %{run}
 //
 // Do the same run, but now with direct IR generation.
 // REDEFINE: %{option} = "enable-runtime-library=false enable-buffer-initialization=true"
 // RUN: %{compile} | %{run}
 //

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_complex64.mlir

 // DEFINE: %{option} = enable-runtime-library=true
 // DEFINE: %{compile} = mlir-opt %s --sparse-compiler=%{option}
 // DEFINE: %{run} = mlir-cpu-runner \
 // DEFINE:  -e entry -entry-point-result=void  \
-// DEFINE:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// DEFINE:  -shared-libs=%mlir_c_runner_utils | \
 // DEFINE: FileCheck %s
 //
 // RUN: %{compile} | %{run}
 //
 // Do the same run, but now with direct IR generation.
 // REDEFINE: %{option} = enable-runtime-library=false
 // RUN: %{compile} | %{run}
 //

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_complex_ops.mlir

 // DEFINE: %{option} = enable-runtime-library=true
 // DEFINE: %{compile} = mlir-opt %s --sparse-compiler=%{option}
 // DEFINE: %{run} = mlir-cpu-runner \
 // DEFINE:  -e entry -entry-point-result=void  \
-// DEFINE:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// DEFINE:  -shared-libs=%mlir_c_runner_utils | \
 // DEFINE: FileCheck %s
 //
 // RUN: %{compile} | %{run}
 //
 // Do the same run, but now with direct IR generation.
 // REDEFINE: %{option} = enable-runtime-library=false
 // RUN: %{compile} | %{run}
 //

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_constant_to_sparse_tensor.mlir

 // DEFINE: %{option} = enable-runtime-library=true
 // DEFINE: %{compile} = mlir-opt %s --sparse-compiler=%{option}
 // DEFINE: %{run} = mlir-cpu-runner \
 // DEFINE:  -e entry -entry-point-result=void  \
-// DEFINE:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// DEFINE:  -shared-libs=%mlir_c_runner_utils | \
 // DEFINE: FileCheck %s
 //
 // RUN: %{compile} | %{run}
 //
 // Do the same run, but now with direct IR generation.
 // REDEFINE: %{option} = "enable-runtime-library=false enable-buffer-initialization=true"
 // RUN: %{compile} | %{run}
 //

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_conv_1d_nwc_wcf.mlir

 // DEFINE: %{option} = enable-runtime-library=true
 // DEFINE: %{compile} = mlir-opt %s --sparse-compiler=%{option}
 // DEFINE: %{run} = mlir-cpu-runner \
 // DEFINE:  -e entry -entry-point-result=void  \
-// DEFINE:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// DEFINE:  -shared-libs=%mlir_c_runner_utils | \
 // DEFINE: FileCheck %s
 //
 // RUN: %{compile} | %{run}
 //
 // Do the same run, but now with direct IR generation.
 // REDEFINE: %{option} = "enable-runtime-library=false enable-buffer-initialization=true"
 // RUN: %{compile} | %{run}
 //

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_conv_2d.mlir

 // DEFINE: %{option} = enable-runtime-library=true
 // DEFINE: %{compile} = mlir-opt %s --sparse-compiler=%{option}
 // DEFINE: %{run} = mlir-cpu-runner \
 // DEFINE:  -e entry -entry-point-result=void  \
-// DEFINE:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// DEFINE:  -shared-libs=%mlir_c_runner_utils | \
 // DEFINE: FileCheck %s
 //
 // RUN: %{compile} | %{run}
 //
 // Do the same run, but now with direct IR generation.
 // REDEFINE: %{option} = "enable-runtime-library=false enable-buffer-initialization=true"
 // RUN: %{compile} | %{run}
 //

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_conv_2d_nhwc_hwcf.mlir

 // DEFINE: %{option} = enable-runtime-library=true
 // DEFINE: %{compile} = mlir-opt %s --sparse-compiler=%{option}
 // DEFINE: %{run} = mlir-cpu-runner \
 // DEFINE:  -e entry -entry-point-result=void  \
-// DEFINE:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// DEFINE:  -shared-libs=%mlir_c_runner_utils | \
 // DEFINE: FileCheck %s
 //
 // RUN: %{compile} | %{run}
 //
 // Do the same run, but now with direct IR generation.
 // REDEFINE: %{option} = "enable-runtime-library=false enable-buffer-initialization=true"
 // RUN: %{compile} | %{run}
 //

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_conv_3d.mlir

 // DEFINE: %{option} = enable-runtime-library=true
 // DEFINE: %{compile} = mlir-opt %s --sparse-compiler=%{option}
 // DEFINE: %{run} = mlir-cpu-runner \
 // DEFINE:  -e entry -entry-point-result=void  \
-// DEFINE:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// DEFINE:  -shared-libs=%mlir_c_runner_utils | \
 // DEFINE: FileCheck %s
 //
 // RUN: %{compile} | %{run}
 //
 // Do the same run, but now with direct IR generation.
 // REDEFINE: %{option} = "enable-runtime-library=false enable-buffer-initialization=true"
 // RUN: %{compile} | %{run}
 //

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_conv_3d_ndhwc_dhwcf.mlir

 // DEFINE: %{option} = enable-runtime-library=true
 // DEFINE: %{compile} = mlir-opt %s --sparse-compiler=%{option}
 // DEFINE: %{run} = mlir-cpu-runner \
 // DEFINE:  -e entry -entry-point-result=void  \
-// DEFINE:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// DEFINE:  -shared-libs=%mlir_c_runner_utils | \
 // DEFINE: FileCheck %s
 //
 // RUN: %{compile} | %{run}
 //
 // Do the same run, but now with direct IR generation.
 // REDEFINE: %{option} = "enable-runtime-library=false enable-buffer-initialization=true"
 // RUN: %{compile} | %{run}
 //

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_conversion.mlir

 // DEFINE: %{option} = enable-runtime-library=true
 // DEFINE: %{compile} = mlir-opt %s --sparse-compiler=%{option}
 // DEFINE: %{run} = mlir-cpu-runner \
 // DEFINE:  -e entry -entry-point-result=void  \
-// DEFINE:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// DEFINE:  -shared-libs=%mlir_c_runner_utils | \
 // DEFINE: FileCheck %s
 //
 // RUN: %{compile} | %{run}
 //
 // Do the same run, but now with direct IR generation.
 // REDEFINE: %{option} = "enable-runtime-library=false enable-buffer-initialization=true"
 // RUN: %{compile} | %{run}
 //

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_conversion_dyn.mlir

 // DEFINE: %{option} = enable-runtime-library=true
 // DEFINE: %{compile} = mlir-opt %s --sparse-compiler=%{option}
 // DEFINE: %{run} = mlir-cpu-runner \
 // DEFINE:  -e entry -entry-point-result=void  \
-// DEFINE:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext,%mlir_lib_dir/libmlir_runner_utils%shlibext | \
+// DEFINE:  -shared-libs=%mlir_c_runner_utils,%mlir_runner_utils | \
 // DEFINE: FileCheck %s
 //
 // RUN: %{compile} | %{run}
 //
 // Do the same run, but now with direct IR generation.
 // REDEFINE: %{option} = "enable-runtime-library=false enable-buffer-initialization=true"
 // RUN: %{compile} | %{run}
 //
 // Do the same run, but now with direct IR generation and vectorization.
 // REDEFINE: %{option} = "enable-runtime-library=false enable-buffer-initialization=true vl=2 reassociate-fp-reductions=true enable-index-optimizations=true"
 // RUN: %{compile} | %{run}
 
 // Do the same run, but now with direct IR generation and, if available, VLA
 // vectorization.
 // REDEFINE: %{option} = "enable-runtime-library=false enable-buffer-initialization=true vl=4 reassociate-fp-reductions=true enable-index-optimizations=true enable-arm-sve=%ENABLE_VLA"
 // REDEFINE: %{run} = %lli \
 // REDEFINE:   --entry-function=entry_lli \
 // REDEFINE:   --extra-module=%S/Inputs/main_for_lli.ll \
 // REDEFINE:   %VLA_ARCH_ATTR_OPTIONS \
-// REDEFINE:   --dlopen=%mlir_native_utils_lib_dir/libmlir_c_runner_utils%shlibext --dlopen=%mlir_lib_dir/libmlir_runner_utils%shlibext | \
+// REDEFINE:   --dlopen=%mlir_native_utils_lib_dir/libmlir_c_runner_utils%shlibext --dlopen=%mlir_runner_utils | \
 // REDEFINE: FileCheck %s
 // RUN: %{compile} | mlir-translate -mlir-to-llvmir | %{run}
 
 #DCSR  = #sparse_tensor.encoding<{
   dimLevelType = [ "compressed", "compressed" ]
 }>
 
 #DCSC  = #sparse_tensor.encoding<{

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_conversion_ptr.mlir

 // DEFINE: %{option} = enable-runtime-library=true
 // DEFINE: %{compile} = mlir-opt %s --sparse-compiler=%{option}
 // DEFINE: %{run} = mlir-cpu-runner \
 // DEFINE:  -e entry -entry-point-result=void  \
-// DEFINE:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext,%mlir_lib_dir/libmlir_runner_utils%shlibext | \
+// DEFINE:  -shared-libs=%mlir_c_runner_utils,%mlir_runner_utils | \
 // DEFINE: FileCheck %s
 //
 // RUN: %{compile} | %{run}
 //
 // Do the same run, but now with direct IR generation.
 // REDEFINE: %{option} = "enable-runtime-library=false enable-buffer-initialization=true"
 // RUN: %{compile} | %{run}
 //

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_conversion_sparse2dense.mlir

 // DEFINE: %{option} = enable-runtime-library=true
 // DEFINE: %{compile} = mlir-opt %s --sparse-compiler=%{option}
 // DEFINE: %{run} = mlir-cpu-runner \
 // DEFINE:  -e entry -entry-point-result=void  \
-// DEFINE:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext,%mlir_lib_dir/libmlir_runner_utils%shlibext | \
+// DEFINE:  -shared-libs=%mlir_c_runner_utils,%mlir_runner_utils | \
 // DEFINE: FileCheck %s
 //
 // RUN: %{compile} | %{run}
 //
 // Do the same run, but now with direct IR generation.
 // REDEFINE: %{option} = enable-runtime-library=false
 // RUN: %{compile} | %{run}
 //

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_conversion_sparse2sparse.mlir

 // Force this file to use the kDirect method for sparse2sparse.
 // DEFINE: %{option} = "enable-runtime-library=true s2s-strategy=2"
 // DEFINE: %{compile} = mlir-opt %s --sparse-compiler=%{option}
 // DEFINE: %{run} = mlir-cpu-runner \
 // DEFINE:  -e entry -entry-point-result=void  \
-// DEFINE:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// DEFINE:  -shared-libs=%mlir_c_runner_utils | \
 // DEFINE: FileCheck %s
 //
 // RUN: %{compile} | %{run}
 //
 // Do the same run, but now with direct IR generation.
 // REDEFINE: %{option} = "enable-runtime-library=false s2s-strategy=2"
 // RUN: %{compile} | %{run}
 //

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_dot.mlir

 // DEFINE: %{option} = enable-runtime-library=true
 // DEFINE: %{compile} = mlir-opt %s --sparse-compiler=%{option}
 // DEFINE: %{run} = mlir-cpu-runner \
 // DEFINE:  -e entry -entry-point-result=void  \
-// DEFINE:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// DEFINE:  -shared-libs=%mlir_c_runner_utils | \
 // DEFINE: FileCheck %s
 //
 // RUN: %{compile} | %{run}
 //
 // Do the same run, but now with direct IR generation.
 // REDEFINE: %{option} = enable-runtime-library=false
 // RUN: %{compile} | %{run}
 //

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_expand.mlir

 // DEFINE: %{option} = enable-runtime-library=true
 // DEFINE: %{compile} = mlir-opt %s --sparse-compiler=%{option}
 // DEFINE: %{run} = mlir-cpu-runner \
 // DEFINE:  -e entry -entry-point-result=void  \
-// DEFINE:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext,%mlir_lib_dir/libmlir_runner_utils%shlibext | \
+// DEFINE:  -shared-libs=%mlir_c_runner_utils,%mlir_runner_utils | \
 // DEFINE: FileCheck %s
 //
 // RUN: %{compile} | %{run}
 //
 // Do the same run, but now with direct IR generation.
 // RUN: %{compile} | %{run}
 //
 // Do the same run, but now with direct IR generation and vectorization.
 // REDEFINE: %{option} = "enable-runtime-library=false vl=2 reassociate-fp-reductions=true enable-index-optimizations=true"
 // RUN: %{compile} | %{run}
 
 // Do the same run, but now with direct IR generation and, if available, VLA
 // vectorization.
 // REDEFINE: %{option} = "enable-runtime-library=false vl=4 enable-arm-sve=%ENABLE_VLA"
 // REDEFINE: %{run} = %lli \
 // REDEFINE:   --entry-function=entry_lli \
 // REDEFINE:   --extra-module=%S/Inputs/main_for_lli.ll \
 // REDEFINE:   %VLA_ARCH_ATTR_OPTIONS \
-// REDEFINE:   --dlopen=%mlir_native_utils_lib_dir/libmlir_c_runner_utils%shlibext --dlopen=%mlir_lib_dir/libmlir_runner_utils%shlibext | \
+// REDEFINE:   --dlopen=%mlir_native_utils_lib_dir/libmlir_c_runner_utils%shlibext --dlopen=%mlir_runner_utils | \
 // REDEFINE: FileCheck %s
 // RUN: %{compile} | mlir-translate -mlir-to-llvmir | %{run}
 
 #CSC = #sparse_tensor.encoding<{
   dimLevelType = [ "dense", "compressed" ],
   dimOrdering = affine_map<(i,j) -> (j,i)>
 }>
 

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_file_io.mlir

 // DEFINE: %{option} = enable-runtime-library=true
 // DEFINE: %{compile} = mlir-opt %s --sparse-compiler=%{option}
 // DEFINE: %{run} = TENSOR0="%mlir_src_dir/test/Integration/data/wide.mtx" TENSOR1="" \
 // DEFINE:   mlir-cpu-runner \
 // DEFINE:  -e entry -entry-point-result=void  \
-// DEFINE:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// DEFINE:  -shared-libs=%mlir_c_runner_utils | \
 // DEFINE: FileCheck %s
 //
 // RUN: %{compile} | %{run}
 //
 // Do the same run, but now with direct IR generation.
 // REDEFINE: %{option} = enable-runtime-library=false
 // RUN: %{compile} | %{run}
 //

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_filter_conv2d.mlir

 // DEFINE: %{option} = enable-runtime-library=true
 // DEFINE: %{compile} = mlir-opt %s --sparse-compiler=%{option}
 // DEFINE: %{run} = mlir-cpu-runner \
 // DEFINE:  -e entry -entry-point-result=void  \
-// DEFINE:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// DEFINE:  -shared-libs=%mlir_c_runner_utils | \
 // DEFINE: FileCheck %s
 //
 // RUN: %{compile} | %{run}
 //
 // Do the same run, but now with direct IR generation.
 // REDEFINE: %{option} = enable-runtime-library=false
 // RUN: %{compile} | %{run}
 //

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_flatten.mlir

 // DEFINE: %{option} = enable-runtime-library=true
 // DEFINE: %{compile} = mlir-opt %s --sparse-compiler=%{option}
 // DEFINE: %{run} = TENSOR0="%mlir_src_dir/test/Integration/data/test.tns" \
 // DEFINE: mlir-cpu-runner \
 // DEFINE:  -e entry -entry-point-result=void  \
-// DEFINE:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext,%mlir_lib_dir/libmlir_runner_utils%shlibext | \
+// DEFINE:  -shared-libs=%mlir_c_runner_utils,%mlir_runner_utils | \
 // DEFINE: FileCheck %s
 //
 // RUN: %{compile} | %{run}
 //
 // Do the same run, but now with direct IR generation.
 // REDEFINE: %{option} = enable-runtime-library=false
 // RUN: %{compile} | %{run}
 //
 // Do the same run, but now with direct IR generation and vectorization.
 // REDEFINE: %{option} = "enable-runtime-library=false vl=2 reassociate-fp-reductions=true enable-index-optimizations=true"
 // RUN: %{compile} | %{run}
 
 // Do the same run, but now with direct IR generation and, if available, VLA
 // vectorization.
 // REDEFINE: %{option} = "enable-runtime-library=false vl=4 enable-arm-sve=%ENABLE_VLA"
 // REDEFINE: %{run} = TENSOR0="%mlir_src_dir/test/Integration/data/test.tns" \
 // REDEFINE: %lli \
 // REDEFINE:   --entry-function=entry_lli \
 // REDEFINE:   --extra-module=%S/Inputs/main_for_lli.ll \
 // REDEFINE:   %VLA_ARCH_ATTR_OPTIONS \
-// REDEFINE:   --dlopen=%mlir_native_utils_lib_dir/libmlir_c_runner_utils%shlibext --dlopen=%mlir_lib_dir/libmlir_runner_utils%shlibext | \
+// REDEFINE:   --dlopen=%mlir_native_utils_lib_dir/libmlir_c_runner_utils%shlibext --dlopen=%mlir_runner_utils | \
 // REDEFINE: FileCheck %s
 // RUN: %{compile} | mlir-translate -mlir-to-llvmir | %{run}
 
 !Filename = !llvm.ptr<i8>
 
 #SparseTensor = #sparse_tensor.encoding<{
   dimLevelType = [ "compressed", "compressed", "compressed", "compressed",
                    "compressed", "compressed", "compressed", "compressed" ],

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_foreach_slices.mlir

 // DEFINE: %{option} = enable-runtime-library=false
 // DEFINE: %{command} = mlir-opt %s --sparse-compiler=%{option} | \
 // DEFINE: mlir-cpu-runner \
 // DEFINE:  -e entry -entry-point-result=void  \
-// DEFINE:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// DEFINE:  -shared-libs=%mlir_c_runner_utils | \
 // DEFINE: FileCheck %s
 //
 // RUN: %{command}
 //
 
 // TODO: support slices on lib path
 #CSR = #sparse_tensor.encoding<{
   dimLevelType = [ "dense", "compressed" ]

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_index.mlir

 // DEFINE: %{option} = enable-runtime-library=true
 // DEFINE: %{compile} = mlir-opt %s --sparse-compiler=%{option}
 // DEFINE: %{run} = mlir-cpu-runner \
 // DEFINE:  -e entry -entry-point-result=void  \
-// DEFINE:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// DEFINE:  -shared-libs=%mlir_c_runner_utils | \
 // DEFINE: FileCheck %s
 //
 // RUN: %{compile} | %{run}
 //
 // Do the same run, but now with direct IR generation.
 // REDEFINE: %{option} = enable-runtime-library=false
 // RUN: %{compile} | %{run}
 //

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_index_dense.mlir

 // DEFINE: %{option} = enable-runtime-library=true
 // DEFINE: %{compile} = mlir-opt %s --sparse-compiler=%{option}
 // DEFINE: %{run} = mlir-cpu-runner \
 // DEFINE:  -e entry -entry-point-result=void  \
-// DEFINE:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// DEFINE:  -shared-libs=%mlir_c_runner_utils | \
 // DEFINE: FileCheck %s
 //
 // RUN: %{compile} | %{run}
 //
 // Do the same run, but now with direct IR generation.
 // REDEFINE: %{option} = enable-runtime-library=false
 // RUN: %{compile} | %{run}
 //

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_insert_1d.mlir

 // DEFINE: %{option} = enable-runtime-library=false
 // DEFINE: %{compile} = mlir-opt %s --sparse-compiler=%{option}
 // DEFINE: %{run} = mlir-cpu-runner \
 // DEFINE:  -e entry -entry-point-result=void  \
-// DEFINE:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// DEFINE:  -shared-libs=%mlir_c_runner_utils | \
 // DEFINE: FileCheck %s
 //
 // RUN: %{compile} | %{run}
 //
 // Do the same run, but now with vectorization.
 // REDEFINE: %{option} = "enable-runtime-library=false vl=2 reassociate-fp-reductions=true enable-index-optimizations=true"
 // RUN: %{compile} | %{run}
 

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_insert_2d.mlir

 // DEFINE: %{option} = enable-runtime-library=false
 // DEFINE: %{compile} = mlir-opt %s --sparse-compiler=%{option}
 // DEFINE: %{run} = mlir-cpu-runner \
 // DEFINE:  -e entry -entry-point-result=void  \
-// DEFINE:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// DEFINE:  -shared-libs=%mlir_c_runner_utils | \
 // DEFINE: FileCheck %s
 //
 // RUN: %{compile} | %{run}
 //
 // Do the same run, but now with vectorization.
 // REDEFINE: %{option} = "enable-runtime-library=false vl=2 reassociate-fp-reductions=true enable-index-optimizations=true"
 // RUN: %{compile} | %{run}
 

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_insert_3d.mlir

 // DEFINE: %{option} = enable-runtime-library=false
 // DEFINE: %{compile} = mlir-opt %s --sparse-compiler=%{option}
 // DEFINE: %{run} = mlir-cpu-runner \
 // DEFINE:  -e entry -entry-point-result=void  \
-// DEFINE:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// DEFINE:  -shared-libs=%mlir_c_runner_utils | \
 // DEFINE: FileCheck %s
 //
 // RUN: %{compile} | %{run}
 //
 // Do the same run, but now with vectorization.
 // REDEFINE: %{option} = "enable-runtime-library=false vl=2 reassociate-fp-reductions=true enable-index-optimizations=true"
 // RUN: %{compile} | %{run}
 

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_matmul.mlir

 // DEFINE: %{option} = enable-runtime-library=true
 // DEFINE: %{compile} = mlir-opt %s --sparse-compiler=%{option}
 // DEFINE: %{run} = mlir-cpu-runner \
 // DEFINE:  -e entry -entry-point-result=void  \
-// DEFINE:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext,%mlir_lib_dir/libmlir_runner_utils%shlibext | \
+// DEFINE:  -shared-libs=%mlir_c_runner_utils,%mlir_runner_utils | \
 // DEFINE: FileCheck %s
 //
 // RUN: %{compile} | %{run}
 //
 // Do the same run, but now with direct IR generation.
 // REDEFINE: %{option} = "enable-runtime-library=false enable-buffer-initialization=true"
 // RUN: %{compile} | %{run}
 //

 
 // Do the same run, but now with direct IR generation and, if available, VLA
 // vectorization.
 // REDEFINE: %{option} = "enable-runtime-library=false vl=4 enable-arm-sve=%ENABLE_VLA"
 // REDEFINE: %{run} = %lli \
 // REDEFINE:   --entry-function=entry_lli \
 // REDEFINE:   --extra-module=%S/Inputs/main_for_lli.ll \
 // REDEFINE:   %VLA_ARCH_ATTR_OPTIONS \
-// REDEFINE:   --dlopen=%mlir_native_utils_lib_dir/libmlir_c_runner_utils%shlibext --dlopen=%mlir_lib_dir/libmlir_runner_utils%shlibext | \
+// REDEFINE:   --dlopen=%mlir_native_utils_lib_dir/libmlir_c_runner_utils%shlibext --dlopen=%mlir_runner_utils | \
 // REDEFINE: FileCheck %s
 // RUN: %{compile} | mlir-translate -mlir-to-llvmir | %{run}
 
 // TODO: Investigate the output generated for SVE, see https://github.com/llvm/llvm-project/issues/60626
 
 #CSR = #sparse_tensor.encoding<{
   dimLevelType = [ "dense", "compressed" ],
   dimOrdering = affine_map<(i,j) -> (i,j)>

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_matrix_ops.mlir

 // DEFINE: %{option} = enable-runtime-library=true
 // DEFINE: %{compile} = mlir-opt %s --sparse-compiler=%{option}
 // DEFINE: %{run} = mlir-cpu-runner \
 // DEFINE:  -e entry -entry-point-result=void  \
-// DEFINE:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext,%mlir_lib_dir/libmlir_runner_utils%shlibext | \
+// DEFINE:  -shared-libs=%mlir_c_runner_utils,%mlir_runner_utils | \
 // DEFINE: FileCheck %s
 //
 // RUN: %{compile} | %{run}
 //
 // Do the same run, but now with direct IR generation.
 // REDEFINE: %{option} = enable-runtime-library=false
 // RUN: %{compile} | %{run}
 //
 // Do the same run, but now with direct IR generation and vectorization.
 // REDEFINE: %{option} = "enable-runtime-library=false vl=2 reassociate-fp-reductions=true enable-index-optimizations=true"
 // RUN: %{compile} | %{run}
 
 // Do the same run, but now with direct IR generation and, if available, VLA
 // vectorization.
 // REDEFINE: %{option} = "enable-runtime-library=false vl=4 enable-arm-sve=%ENABLE_VLA"
 // REDEFINE: %{run} = %lli \
 // REDEFINE:   --entry-function=entry_lli \
 // REDEFINE:   --extra-module=%S/Inputs/main_for_lli.ll \
 // REDEFINE:   %VLA_ARCH_ATTR_OPTIONS \
-// REDEFINE:   --dlopen=%mlir_native_utils_lib_dir/libmlir_c_runner_utils%shlibext --dlopen=%mlir_lib_dir/libmlir_runner_utils%shlibext | \
+// REDEFINE:   --dlopen=%mlir_native_utils_lib_dir/libmlir_c_runner_utils%shlibext --dlopen=%mlir_runner_utils | \
 // REDEFINE: FileCheck %s
 // RUN: %{compile} | mlir-translate -mlir-to-llvmir | %{run}
 
 #DCSR = #sparse_tensor.encoding<{dimLevelType = ["compressed", "compressed"]}>
 
 //
 // Traits for 2-d tensor (aka matrix) operations.
 //

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_matvec.mlir

 // DEFINE: %{option} = enable-runtime-library=true
 // DEFINE: %{compile} = mlir-opt %s --sparse-compiler=%{option}
 // DEFINE: %{run} = TENSOR0="%mlir_src_dir/test/Integration/data/wide.mtx" \
 // DEFINE: mlir-cpu-runner \
 // DEFINE:  -e entry -entry-point-result=void  \
-// DEFINE:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// DEFINE:  -shared-libs=%mlir_c_runner_utils | \
 // DEFINE: FileCheck %s
 // RUN: %{compile} | %{run}
 //
 // Do the same run, but now with direct IR generation.
 // REDEFINE: %{option} = enable-runtime-library=false
 // RUN: %{compile} | %{run}
 //
 // Do the same run, but now with parallelization strategy.

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_mttkrp.mlir

 // DEFINE: %{option} = enable-runtime-library=true
 // DEFINE: %{compile} = mlir-opt %s --sparse-compiler=%{option}
 // DEFINE: %{run} = TENSOR0="%mlir_src_dir/test/Integration/data/mttkrp_b.tns"  \
 // DEFINE: mlir-cpu-runner \
 // DEFINE:  -e entry -entry-point-result=void  \
-// DEFINE:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext,%mlir_lib_dir/libmlir_runner_utils%shlibext | \
+// DEFINE:  -shared-libs=%mlir_c_runner_utils,%mlir_runner_utils | \
 // DEFINE: FileCheck %s
 //
 // RUN: %{compile} | %{run}
 //
 // Do the same run, but now with direct IR generation.
 // REDEFINE: %{option} = enable-runtime-library=false
 // RUN: %{compile} | %{run}
 //
 // Do the same run, but now with direct IR generation and vectorization.
 // REDEFINE: %{option} = "enable-runtime-library=false vl=2 reassociate-fp-reductions=true enable-index-optimizations=true"
 // RUN: %{compile} | %{run}
 
 // Do the same run, but now with direct IR generation and, if available, VLA
 // vectorization.
 // REDEFINE: %{option} = "enable-runtime-library=false vl=4  enable-arm-sve=%ENABLE_VLA"
 // REDEFINE: %{run} = TENSOR0="%mlir_src_dir/test/Integration/data/mttkrp_b.tns" \
 // REDEFINE: %lli \
 // REDEFINE:   --entry-function=entry_lli \
 // REDEFINE:   --extra-module=%S/Inputs/main_for_lli.ll \
 // REDEFINE:   %VLA_ARCH_ATTR_OPTIONS \
-// REDEFINE:   --dlopen=%mlir_native_utils_lib_dir/libmlir_c_runner_utils%shlibext -dlopen=%mlir_lib_dir/libmlir_runner_utils%shlibext| \
+// REDEFINE:   --dlopen=%mlir_native_utils_lib_dir/libmlir_c_runner_utils%shlibext -dlopen=%mlir_runner_utils| \
 // REDEFINE: FileCheck %s
 // RUN: %{compile} | mlir-translate -mlir-to-llvmir | %{run}
 
 !Filename = !llvm.ptr<i8>
 
 #SparseTensor = #sparse_tensor.encoding<{
   dimLevelType = [ "compressed", "compressed", "compressed" ]
 }>

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_out_mult_elt.mlir

 // DEFINE: %{option} = enable-runtime-library=true
 // DEFINE: %{compile} = mlir-opt %s --sparse-compiler=%{option}
 // DEFINE: %{run} = mlir-cpu-runner \
 // DEFINE:  -e entry -entry-point-result=void  \
-// DEFINE:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// DEFINE:  -shared-libs=%mlir_c_runner_utils | \
 // DEFINE: FileCheck %s
 //
 // RUN: %{compile} | %{run}
 //
 // Do the same run, but now with direct IR generation.
 // REDEFINE: %{option} = "enable-runtime-library=false enable-buffer-initialization=true"
 // RUN: %{compile} | %{run}
 //

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_out_reduction.mlir

 // DEFINE: %{option} = enable-runtime-library=true
 // DEFINE: %{compile} = mlir-opt %s --sparse-compiler=%{option}
 // DEFINE: %{run} = mlir-cpu-runner \
 // DEFINE:  -e entry -entry-point-result=void  \
-// DEFINE:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// DEFINE:  -shared-libs=%mlir_c_runner_utils | \
 // DEFINE: FileCheck %s
 //
 // RUN: %{compile} | %{run}
 //
 // Do the same run, but now with direct IR generation.
 // REDEFINE: %{option} = "enable-runtime-library=false  enable-buffer-initialization=true"
 // RUN: %{compile} | %{run}
 //

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_out_simple.mlir

 // DEFINE: %{option} = enable-runtime-library=true
 // DEFINE: %{compile} = mlir-opt %s --sparse-compiler=%{option}
 // DEFINE: %{run} = TENSOR0="%mlir_src_dir/test/Integration/data/test.mtx" \
 // DEFINE: mlir-cpu-runner \
 // DEFINE:  -e entry -entry-point-result=void  \
-// DEFINE:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// DEFINE:  -shared-libs=%mlir_c_runner_utils | \
 // DEFINE: FileCheck %s
 //
 // RUN: %{compile} | %{run}
 //
 // Do the same run, but now with direct IR generation.
 // REDEFINE: %{option} = enable-runtime-library=false
 // RUN: %{compile} | %{run}
 //

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_pack.mlir

 // DEFINE: %{option} = enable-runtime-library=false
 // DEFINE: %{compile} = mlir-opt %s --sparse-compiler=%{option}
 // DEFINE: %{run} = mlir-cpu-runner \
 // DEFINE:  -e entry -entry-point-result=void  \
-// DEFINE:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// DEFINE:  -shared-libs=%mlir_c_runner_utils | \
 // DEFINE: FileCheck %s
 //
 // RUN: %{compile} | %{run}
 //
 
 // Do the same run, but now with direct IR generation and, if available, VLA
 // vectorization.
 // REDEFINE: %{option} = "enable-runtime-library=false vl=4 enable-arm-sve=%ENABLE_VLA"

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_quantized_matmul.mlir

 // DEFINE: %{option} = enable-runtime-library=true
 // DEFINE: %{compile} = mlir-opt %s --sparse-compiler=%{option}
 // DEFINE: %{run} = mlir-cpu-runner \
 // DEFINE:  -e entry -entry-point-result=void  \
-// DEFINE:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// DEFINE:  -shared-libs=%mlir_c_runner_utils | \
 // DEFINE: FileCheck %s
 //
 // RUN: %{compile} | %{run}
 //
 // Do the same run, but now with direct IR generation.
 // REDEFINE: %{option} = enable-runtime-library=false
 // RUN: %{compile} | %{run}
 //

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_re_im.mlir

 // DEFINE: %{option} = enable-runtime-library=true
 // DEFINE: %{compile} = mlir-opt %s --sparse-compiler=%{option}
 // DEFINE: %{run} = mlir-cpu-runner \
 // DEFINE:  -e entry -entry-point-result=void  \
-// DEFINE:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// DEFINE:  -shared-libs=%mlir_c_runner_utils | \
 // DEFINE: FileCheck %s
 //
 // RUN: %{compile} | %{run}
 //
 // Do the same run, but now with direct IR generation.
 // REDEFINE: %{option} = enable-runtime-library=false
 // RUN: %{compile} | %{run}
 //

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_reduce_custom.mlir

 // DEFINE: %{option} = enable-runtime-library=true
 // DEFINE: %{compile} = mlir-opt %s --sparse-compiler=%{option}
 // DEFINE: %{run} = mlir-cpu-runner \
 // DEFINE:  -e entry -entry-point-result=void  \
-// DEFINE:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// DEFINE:  -shared-libs=%mlir_c_runner_utils | \
 // DEFINE: FileCheck %s
 //
 // RUN: %{compile} | %{run}
 //
 // Do the same run, but now with direct IR generation.
 // REDEFINE: %{option} = "enable-runtime-library=false enable-buffer-initialization=true"
 // RUN: %{compile} | %{run}
 //

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_reduce_custom_prod.mlir

 // DEFINE: %{option} = enable-runtime-library=true
 // DEFINE: %{compile} = mlir-opt %s --sparse-compiler=%{option}
 // DEFINE: %{run} = mlir-cpu-runner \
 // DEFINE:  -e entry -entry-point-result=void  \
-// DEFINE:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// DEFINE:  -shared-libs=%mlir_c_runner_utils | \
 // DEFINE: FileCheck %s
 //
 // RUN: %{compile} | %{run}
 //
 // Do the same run, but now with direct IR generation.
 // REDEFINE: %{option} = "enable-runtime-library=false enable-buffer-initialization=true"
 // RUN: %{compile} | %{run}
 //

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_reductions.mlir

 // DEFINE: %{option} = enable-runtime-library=true
 // DEFINE: %{compile} = mlir-opt %s --sparse-compiler=%{option}
 // DEFINE: %{run} = mlir-cpu-runner \
 // DEFINE:  -e entry -entry-point-result=void  \
-// DEFINE:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// DEFINE:  -shared-libs=%mlir_c_runner_utils | \
 // DEFINE: FileCheck %s
 //
 // RUN: %{compile} | %{run}
 //
 // Do the same run, but now with direct IR generation.
 // REDEFINE: %{option} = enable-runtime-library=false
 // RUN: %{compile} | %{run}
 //

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_reductions_prod.mlir

 // DEFINE: %{option} = enable-runtime-library=true
 // DEFINE: %{command} = mlir-opt %s --sparse-compiler=%{option} | \
 // DEFINE: mlir-cpu-runner \
 // DEFINE:  -e entry -entry-point-result=void  \
-// DEFINE:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// DEFINE:  -shared-libs=%mlir_c_runner_utils | \
 // DEFINE: FileCheck %s
 //
 // RUN: %{command}
 //
 // Do the same run, but now with direct IR generation.
 // REDEFINE: %{option} = enable-runtime-library=false
 // RUN: %{command}
 //

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_reshape.mlir

 // DEFINE: %{option} = enable-runtime-library=true
 // DEFINE: %{compile} = mlir-opt %s --sparse-compiler=%{option}
 // DEFINE: %{run} = mlir-cpu-runner \
 // DEFINE:  -e entry -entry-point-result=void  \
-// DEFINE:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// DEFINE:  -shared-libs=%mlir_c_runner_utils | \
 // DEFINE: FileCheck %s
 //
 // RUN: %{compile} | %{run}
 //
 // Do the same run, but now with direct IR generation.
 // REDEFINE: %{option} = enable-runtime-library=false
 // RUN: %{compile} | %{run}
 //

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_rewrite_push_back.mlir

 // DEFINE: %{option} = enable-runtime-library=false
 // DEFINE: %{compile} = mlir-opt %s --sparse-compiler=%{option}
 // DEFINE: %{run} = mlir-cpu-runner \
 // DEFINE:  -e entry -entry-point-result=void  \
-// DEFINE:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// DEFINE:  -shared-libs=%mlir_c_runner_utils | \
 // DEFINE: FileCheck %s
 //
 // RUN: %{compile} | %{run}
 //
 // Do the same run, but now with vectorization.
 // REDEFINE: %{option} = "enable-runtime-library=false vl=2 reassociate-fp-reductions=true enable-index-optimizations=true"
 // RUN: %{compile} | %{run}
 

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_rewrite_sort.mlir

 // DEFINE: %{option} = enable-runtime-library=false
 // DEFINE: %{compile} = mlir-opt %s --sparse-compiler=%{option}
 // DEFINE: %{run} = mlir-cpu-runner \
 // DEFINE:  -e entry -entry-point-result=void  \
-// DEFINE:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext,%mlir_lib_dir/libmlir_runner_utils%shlibext | \
+// DEFINE:  -shared-libs=%mlir_c_runner_utils,%mlir_runner_utils | \
 // DEFINE: FileCheck %s
 //
 // RUN: %{compile} | %{run}
 
 // Do the same run, but now with direct IR generation and, if available, VLA
 // vectorization.
 // REDEFINE: %{option} = "enable-runtime-library=false vl=4 enable-arm-sve=%ENABLE_VLA"
 // REDEFINE: %{run} = %lli \
 // REDEFINE:   --entry-function=entry_lli \
 // REDEFINE:   --extra-module=%S/Inputs/main_for_lli.ll \
 // REDEFINE:   %VLA_ARCH_ATTR_OPTIONS \
-// REDEFINE:   --dlopen=%mlir_native_utils_lib_dir/libmlir_c_runner_utils%shlibext --dlopen=%mlir_lib_dir/libmlir_runner_utils%shlibext | \
+// REDEFINE:   --dlopen=%mlir_native_utils_lib_dir/libmlir_c_runner_utils%shlibext --dlopen=%mlir_runner_utils | \
 // REDEFINE: FileCheck %s
 // RUN: %{compile} | mlir-translate -mlir-to-llvmir | %{run}
 
 module {
   func.func private @printMemref1dI32(%ptr : memref<?xi32>) attributes { llvm.emit_c_interface }
 
   // Stores 5 values to the memref buffer.
   func.func @storeValuesTo(%b: memref<?xi32>, %v0: i32, %v1: i32, %v2: i32,

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_rewrite_sort_coo.mlir

 // DEFINE: %{option} = enable-runtime-library=false
 // DEFINE: %{compile} = mlir-opt %s --sparse-compiler=%{option}
 // DEFINE: %{run} = mlir-cpu-runner \
 // DEFINE:  -e entry -entry-point-result=void  \
-// DEFINE:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// DEFINE:  -shared-libs=%mlir_c_runner_utils | \
 // DEFINE: FileCheck %s
 //
 // RUN: %{compile} | %{run}
 //
 // Do the same run, but now with vectorization.
 // REDEFINE: %{option} = "enable-runtime-library=false vl=2 reassociate-fp-reductions=true enable-index-optimizations=true"
 // RUN: %{compile} | %{run}
 

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_sampled_matmul.mlir

 // DEFINE: %{option} = enable-runtime-library=true
 // DEFINE: %{compile} = mlir-opt %s --sparse-compiler=%{option}
 // DEFINE: %{run} = TENSOR0="%mlir_src_dir/test/Integration/data/test.mtx" \
 // DEFINE: mlir-cpu-runner \
 // DEFINE:  -e entry -entry-point-result=void  \
-// DEFINE:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// DEFINE:  -shared-libs=%mlir_c_runner_utils | \
 // DEFINE: FileCheck %s
 //
 // RUN: %{compile} | %{run}
 //
 // Do the same run, but now with direct IR generation.
 // REDEFINE: %{option} = enable-runtime-library=false
 // RUN: %{compile} | %{run}
 //
 // Do the same run, but now with direct IR generation and vectorization.
 // REDEFINE: %{option} = "enable-runtime-library=false vl=2 reassociate-fp-reductions=true enable-index-optimizations=true"
 // RUN: %{compile} | %{run}
 
 // Do the same run, but now with direct IR generation and, if available, VLA
 // vectorization.
 // REDEFINE: %{option} = "enable-runtime-library=false vl=4  enable-arm-sve=%ENABLE_VLA"
 // REDEFINE: %{run} = TENSOR0="%mlir_src_dir/test/Integration/data/test.mtx" \
 // REDEFINE: %lli \
 // REDEFINE:   --entry-function=entry_lli \
 // REDEFINE:   --extra-module=%S/Inputs/main_for_lli.ll \
 // REDEFINE:   %VLA_ARCH_ATTR_OPTIONS \
 // REDEFINE:   --dlopen=%mlir_native_utils_lib_dir/libmlir_c_runner_utils%shlibext | \
 // REDEFINE: FileCheck %s
 // RUN: %{compile} | mlir-translate -mlir-to-llvmir | %{run}
 
 !Filename = !llvm.ptr<i8>
 
 #SparseMatrix = #sparse_tensor.encoding<{
   dimLevelType = [ "compressed", "compressed" ],
   pointerBitWidth = 32,

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_sampled_mm_fusion.mlir

 // DEFINE: %{option} = enable-runtime-library=true
 // DEFINE: %{compile} = mlir-opt %s --sparse-compiler=%{option}
 // DEFINE: %{run} = mlir-cpu-runner \
 // DEFINE:  -e entry -entry-point-result=void  \
-// DEFINE:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// DEFINE:  -shared-libs=%mlir_c_runner_utils | \
 // DEFINE: FileCheck %s
 //
 // RUN: %{compile} | %{run}
 //
 // Do the same run, but now with direct IR generation.
 // REDEFINE: %{option} = "enable-runtime-library=false enable-buffer-initialization=true"
 // RUN: %{compile} | %{run}
 //

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_scale.mlir

 // DEFINE: %{option} = enable-runtime-library=true
 // DEFINE: %{compile} = mlir-opt %s --sparse-compiler=%{option}
 // DEFINE: %{run} = mlir-cpu-runner \
 // DEFINE:  -e entry -entry-point-result=void  \
-// DEFINE:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// DEFINE:  -shared-libs=%mlir_c_runner_utils | \
 // DEFINE: FileCheck %s
 //
 // RUN: %{compile} | %{run}
 //
 // Do the same run, but now with direct IR generation.
 // REDEFINE: %{option} = enable-runtime-library=false
 // RUN: %{compile} | %{run}
 

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_scf_nested.mlir

 // DEFINE: %{option} = enable-runtime-library=true
 // DEFINE: %{compile} = mlir-opt %s --sparse-compiler=%{option}
 // DEFINE: %{run} = mlir-cpu-runner \
 // DEFINE:  -e entry -entry-point-result=void  \
-// DEFINE:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// DEFINE:  -shared-libs=%mlir_c_runner_utils | \
 // DEFINE: FileCheck %s
 //
 // RUN: %{compile} | %{run}
 //
 // Do the same run, but now with direct IR generation.
 // REDEFINE: %{option} = enable-runtime-library=false
 // RUN: %{compile} | %{run}
 

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_select.mlir

 // DEFINE: %{option} = enable-runtime-library=true
 // DEFINE: %{compile} = mlir-opt %s --sparse-compiler=%{option}
 // DEFINE: %{run} = mlir-cpu-runner \
 // DEFINE:  -e entry -entry-point-result=void  \
-// DEFINE:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// DEFINE:  -shared-libs=%mlir_c_runner_utils | \
 // DEFINE: FileCheck %s
 //
 // RUN: %{compile} | %{run}
 //
 // Do the same run, but now with direct IR generation.
 // REDEFINE: %{option} = "enable-runtime-library=false enable-buffer-initialization=true"
 // RUN: %{compile} | %{run}
 

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_sign.mlir

 // DEFINE: %{option} = enable-runtime-library=true
 // DEFINE: %{compile} = mlir-opt %s --sparse-compiler=%{option}
 // DEFINE: %{run} = mlir-cpu-runner \
 // DEFINE:  -e entry -entry-point-result=void  \
-// DEFINE:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// DEFINE:  -shared-libs=%mlir_c_runner_utils | \
 // DEFINE: FileCheck %s
 //
 // RUN: %{compile} | %{run}
 //
 // Do the same run, but now with direct IR generation.
 // REDEFINE: %{option} = "enable-runtime-library=false enable-buffer-initialization=true"
 // RUN: %{compile} | %{run}
 

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

 // DEFINE: %{option} = enable-runtime-library=true
 // DEFINE: %{compile} = mlir-opt %s --sparse-compiler=%{option}
 // DEFINE: %{run} = TENSOR0="%mlir_src_dir/test/Integration/data/wide.mtx" \
 // DEFINE: TENSOR1="%mlir_src_dir/test/Integration/data/mttkrp_b.tns" \
 // DEFINE: mlir-cpu-runner \
 // DEFINE:  -e entry -entry-point-result=void  \
-// DEFINE:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// DEFINE:  -shared-libs=%mlir_c_runner_utils | \
 // DEFINE: FileCheck %s
 //
 // RUN: %{compile} | %{run}
 //
 // Do the same run, but now with direct IR generation.
 // REDEFINE: %{option} = "enable-runtime-library=false enable-buffer-initialization=true"
 // RUN: %{compile} | %{run}
 

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

 // DEFINE: %{option} = enable-runtime-library=true
 // DEFINE: %{compile} = mlir-opt %s --sparse-compiler=%{option}
 // DEFINE: %{run} = TENSOR0="%mlir_src_dir/test/Integration/data/wide.mtx" \
 // DEFINE: mlir-cpu-runner \
 // DEFINE:  -e entry -entry-point-result=void  \
-// DEFINE:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// DEFINE:  -shared-libs=%mlir_c_runner_utils | \
 // DEFINE: FileCheck %s
 //
 // RUN: %{compile} | %{run}
 //
 // Do the same run, but now with direct IR generation.
 // REDEFINE: %{option} = enable-runtime-library=false
 // RUN: %{compile} | %{run}
 //

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_storage.mlir

 // DEFINE: %{option} = enable-runtime-library=true
 // DEFINE: %{compile} = mlir-opt %s --sparse-compiler=%{option}
 // DEFINE: %{run} = mlir-cpu-runner \
 // DEFINE:  -e entry -entry-point-result=void  \
-// DEFINE:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// DEFINE:  -shared-libs=%mlir_c_runner_utils | \
 // DEFINE: FileCheck %s
 //
 // RUN: %{compile} | %{run}
 //
 // Do the same run, but now with direct IR generation.
 // REDEFINE: %{option} = enable-runtime-library=false
 // RUN: %{compile} | %{run}
 //

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_sum.mlir

 // DEFINE: %{option} = enable-runtime-library=true
 // DEFINE: %{compile} = mlir-opt %s --sparse-compiler=%{option}
 // DEFINE: %{run} = TENSOR0="%mlir_src_dir/test/Integration/data/test_symmetric.mtx" \
 // DEFINE: mlir-cpu-runner \
 // DEFINE:  -e entry -entry-point-result=void  \
-// DEFINE:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// DEFINE:  -shared-libs=%mlir_c_runner_utils | \
 // DEFINE: FileCheck %s
 //
 // RUN: %{compile} | %{run}
 //
 // Do the same run, but now with direct IR generation.
 // REDEFINE: %{option} = enable-runtime-library=false
 // RUN: %{compile} | %{run}
 //

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_sum_bf16.mlir

 // DEFINE: %{option} = enable-runtime-library=true
 // DEFINE: %{command} = mlir-opt %s --sparse-compiler=%{option} | \
 // DEFINE: mlir-cpu-runner \
 // DEFINE:  -e entry -entry-point-result=void  \
-// DEFINE:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// DEFINE:  -shared-libs=%mlir_c_runner_utils | \
 // DEFINE: FileCheck %s
 //
 // RUN: %{command}
 //
 // Do the same run, but now with direct IR generation.
 // REDEFINE: %{option} = enable-runtime-library=false
 // RUN: %{command}
 //

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_sum_c32.mlir

 // DEFINE: %{option} = enable-runtime-library=true
 // DEFINE: %{compile} = mlir-opt %s --sparse-compiler=%{option}
 // DEFINE: %{run} = TENSOR0="%mlir_src_dir/test/Integration/data/test_symmetric_complex.mtx" \
 // DEFINE: mlir-cpu-runner \
 // DEFINE:  -e entry -entry-point-result=void  \
-// DEFINE:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// DEFINE:  -shared-libs=%mlir_c_runner_utils | \
 // DEFINE: FileCheck %s
 //
 // RUN: %{compile} | %{run}
 //
 // Do the same run, but now with direct IR generation.
 // REDEFINE: %{option} = enable-runtime-library=false
 // RUN: %{compile} | %{run}
 //

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_sum_f16.mlir

 // DEFINE: %{option} = enable-runtime-library=true
 // DEFINE: %{compile} = mlir-opt %s --sparse-compiler=%{option}
 // DEFINE: %{run} = mlir-cpu-runner \
 // DEFINE:  -e entry -entry-point-result=void  \
-// DEFINE:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// DEFINE:  -shared-libs=%mlir_c_runner_utils | \
 // DEFINE: FileCheck %s
 //
 // RUN: %{compile} | %{run}
 //
 // Do the same run, but now with direct IR generation.
 // REDEFINE: %{option} = enable-runtime-library=false
 // RUN: %{compile} | %{run}
 //

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_tanh.mlir

 // DEFINE: %{option} = enable-runtime-library=true
 // DEFINE: %{compile} = mlir-opt %s --sparse-compiler=%{option}
 // DEFINE: %{run} = mlir-cpu-runner \
 // DEFINE:  -e entry -entry-point-result=void  \
-// DEFINE:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// DEFINE:  -shared-libs=%mlir_c_runner_utils | \
 // DEFINE: FileCheck %s
 //
 // RUN: %{compile} | %{run}
 //
 // Do the same run, but now with direct IR generation.
 // REDEFINE: %{option} = enable-runtime-library=false
 // RUN: %{compile} | %{run}
 //

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_tensor_mul.mlir

 // DEFINE: %{option} = enable-runtime-library=true
 // DEFINE: %{compile} = mlir-opt %s --sparse-compiler=%{option}
 // DEFINE: %{run} = mlir-cpu-runner \
 // DEFINE:  -e entry -entry-point-result=void  \
-// DEFINE:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// DEFINE:  -shared-libs=%mlir_c_runner_utils | \
 // DEFINE: FileCheck %s
 //
 // RUN: %{compile} | %{run}
 //
 // Do the same run, but now with direct IR generation.
 // REDEFINE: %{option} = enable-runtime-library=false
 // RUN: %{compile} | %{run}
 //

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_tensor_ops.mlir

 // DEFINE: %{option} = enable-runtime-library=true
 // DEFINE: %{compile} = mlir-opt %s --sparse-compiler=%{option}
 // DEFINE: %{run} = mlir-cpu-runner \
 // DEFINE:  -e entry -entry-point-result=void  \
-// DEFINE:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// DEFINE:  -shared-libs=%mlir_c_runner_utils | \
 // DEFINE: FileCheck %s
 //
 // RUN: %{compile} | %{run}
 //
 // Do the same run, but now with direct IR generation.
 // REDEFINE: %{option} = enable-runtime-library=false
 // RUN: %{compile} | %{run}
 //

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_transpose.mlir

 // DEFINE: %{option} = enable-runtime-library=true
 // DEFINE: %{compile} = mlir-opt %s --sparse-compiler=%{option}
 // DEFINE: %{run} = mlir-cpu-runner \
 // DEFINE:  -e entry -entry-point-result=void  \
-// DEFINE:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// DEFINE:  -shared-libs=%mlir_c_runner_utils | \
 // DEFINE: FileCheck %s
 //
 // RUN: %{compile} | %{run}
 //
 // Do the same run, but now with direct IR generation.
 // REDEFINE: %{option} = "enable-runtime-library=false enable-buffer-initialization=true"
 // RUN: %{compile} | %{run}
 //

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_unary.mlir

 // DEFINE: %{option} = enable-runtime-library=true
 // DEFINE: %{compile} = mlir-opt %s --sparse-compiler=%{option}
 // DEFINE: %{run} = mlir-cpu-runner \
 // DEFINE:  -e entry -entry-point-result=void  \
-// DEFINE:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// DEFINE:  -shared-libs=%mlir_c_runner_utils | \
 // DEFINE: FileCheck %s
 //
 // RUN: %{compile} | %{run}
 //
 // Do the same run, but now with direct IR generation.
 // REDEFINE: %{option} = "enable-runtime-library=false enable-buffer-initialization=true"
 // RUN: %{compile} | %{run}
 //

mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_vector_ops.mlir

 // DEFINE: %{option} = enable-runtime-library=true
 // DEFINE: %{compile} = mlir-opt %s --sparse-compiler=%{option}
 // DEFINE: %{run} = mlir-cpu-runner \
 // DEFINE:  -e entry -entry-point-result=void  \
-// DEFINE:  -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// DEFINE:  -shared-libs=%mlir_c_runner_utils | \
 // DEFINE: FileCheck %s
 //
 // RUN: %{compile} | %{run}
 //
 // Do the same run, but now with direct IR generation.
 // REDEFINE: %{option} = "enable-runtime-library=false enable-buffer-initialization=true"
 // RUN: %{compile} | %{run}
 //

mlir/test/Integration/Dialect/SparseTensor/python/test_SDDMM.py

-# RUN: SUPPORT_LIB=%mlir_lib_dir/libmlir_c_runner_utils%shlibext \
+# RUN: env SUPPORT_LIB=%mlir_c_runner_utils \
 # RUN:   %PYTHON %s | FileCheck %s
 
 import ctypes
 import numpy as np
 import os
 import sys
 
 from mlir import ir

mlir/test/Integration/Dialect/SparseTensor/python/test_SpMM.py

-# RUN: SUPPORT_LIB=%mlir_lib_dir/libmlir_c_runner_utils%shlibext \
+# RUN: env SUPPORT_LIB=%mlir_c_runner_utils \
 # RUN:   %PYTHON %s | FileCheck %s
 
 import ctypes
 import numpy as np
 import os
 import sys
 
 from mlir import ir

mlir/test/Integration/Dialect/SparseTensor/python/test_elementwise_add_sparse_output.py

-# RUN: SUPPORT_LIB=%mlir_lib_dir/libmlir_c_runner_utils%shlibext %PYTHON %s | FileCheck %s
+# RUN: env SUPPORT_LIB=%mlir_c_runner_utils %PYTHON %s | FileCheck %s
 
 import ctypes
 import numpy as np
 import os
 import sys
 
 from mlir import ir
 from mlir import runtime as rt

mlir/test/Integration/Dialect/SparseTensor/python/test_output.py

-# RUN: SUPPORT_LIB=%mlir_lib_dir/libmlir_c_runner_utils%shlibext \
+# RUN: env SUPPORT_LIB=%mlir_c_runner_utils \
 # RUN:   %PYTHON %s | FileCheck %s
 
 import ctypes
 import os
 import sys
 import tempfile
 
 from mlir import ir

mlir/test/Integration/Dialect/SparseTensor/python/test_stress.py

-# RUN: SUPPORT_LIB=%mlir_lib_dir/libmlir_c_runner_utils%shlibext \
+# RUN: env SUPPORT_LIB=%mlir_c_runner_utils \
 # RUN:   %PYTHON %s | FileCheck %s
 
 import ctypes
 import errno
 import itertools
 import os
 import sys
 

mlir/test/Integration/Dialect/SparseTensor/taco/test_MTTKRP.py

-# RUN: SUPPORTLIB=%mlir_lib_dir/libmlir_c_runner_utils%shlibext %PYTHON %s | FileCheck %s
+# RUN: env SUPPORTLIB=%mlir_c_runner_utils %PYTHON %s | FileCheck %s
 
 import numpy as np
 import os
 import sys
 import tempfile
 
 _SCRIPT_PATH = os.path.dirname(os.path.abspath(__file__))
 sys.path.append(_SCRIPT_PATH)

mlir/test/Integration/Dialect/SparseTensor/taco/test_SDDMM.py

-# RUN: SUPPORTLIB=%mlir_lib_dir/libmlir_c_runner_utils%shlibext %PYTHON %s | FileCheck %s
+# RUN: env SUPPORTLIB=%mlir_c_runner_utils %PYTHON %s | FileCheck %s
 
 import filecmp
 import numpy as np
 import os
 import sys
 import tempfile
 
 _SCRIPT_PATH = os.path.dirname(os.path.abspath(__file__))

mlir/test/Integration/Dialect/SparseTensor/taco/test_SpMM.py

-# RUN: SUPPORTLIB=%mlir_lib_dir/libmlir_c_runner_utils%shlibext %PYTHON %s | FileCheck %s
+# RUN: env SUPPORTLIB=%mlir_c_runner_utils %PYTHON %s | FileCheck %s
 
 import filecmp
 import numpy as np
 import os
 import sys
 import tempfile
 
 _SCRIPT_PATH = os.path.dirname(os.path.abspath(__file__))

mlir/test/Integration/Dialect/SparseTensor/taco/test_SpMV.py

-# RUN: SUPPORTLIB=%mlir_lib_dir/libmlir_c_runner_utils%shlibext %PYTHON %s | FileCheck %s
+# RUN: env SUPPORTLIB=%mlir_c_runner_utils %PYTHON %s | FileCheck %s
 
 import numpy as np
 import os
 import sys
 import tempfile
 
 _SCRIPT_PATH = os.path.dirname(os.path.abspath(__file__))
 sys.path.append(_SCRIPT_PATH)

mlir/test/Integration/Dialect/SparseTensor/taco/test_Tensor.py

-# RUN: SUPPORTLIB=%mlir_lib_dir/libmlir_c_runner_utils%shlibext %PYTHON %s | FileCheck %s
+# RUN: env SUPPORTLIB=%mlir_c_runner_utils %PYTHON %s | FileCheck %s
 
 import filecmp
 import numpy as np
 import os
 import sys
 import tempfile
 
 _SCRIPT_PATH = os.path.dirname(os.path.abspath(__file__))

mlir/test/Integration/Dialect/SparseTensor/taco/test_scalar_tensor_algebra.py

-# RUN: SUPPORTLIB=%mlir_lib_dir/libmlir_c_runner_utils%shlibext %PYTHON %s | FileCheck %s
+# RUN: env SUPPORTLIB=%mlir_c_runner_utils %PYTHON %s | FileCheck %s
 
 import numpy as np
 import os
 import sys
 
 _SCRIPT_PATH = os.path.dirname(os.path.abspath(__file__))
 sys.path.append(_SCRIPT_PATH)
 from tools import mlir_pytaco_api as pt

mlir/test/Integration/Dialect/SparseTensor/taco/test_simple_tensor_algebra.py

-# RUN: SUPPORTLIB=%mlir_lib_dir/libmlir_c_runner_utils%shlibext %PYTHON %s | FileCheck %s
+# RUN: env SUPPORTLIB=%mlir_c_runner_utils %PYTHON %s | FileCheck %s
 
 import numpy as np
 import os
 import sys
 
 _SCRIPT_PATH = os.path.dirname(os.path.abspath(__file__))
 sys.path.append(_SCRIPT_PATH)
 from tools import mlir_pytaco_api as pt

mlir/test/Integration/Dialect/SparseTensor/taco/test_tensor_complex.py

-# RUN: SUPPORTLIB=%mlir_lib_dir/libmlir_c_runner_utils%shlibext %PYTHON %s | FileCheck %s
+# RUN: env SUPPORTLIB=%mlir_c_runner_utils %PYTHON %s | FileCheck %s
 import numpy as np
 import os
 import sys
 
 _SCRIPT_PATH = os.path.dirname(os.path.abspath(__file__))
 sys.path.append(_SCRIPT_PATH)
 from tools import mlir_pytaco_api as pt
 

mlir/test/Integration/Dialect/SparseTensor/taco/test_tensor_types.py

-# RUN: SUPPORTLIB=%mlir_lib_dir/libmlir_c_runner_utils%shlibext %PYTHON %s | FileCheck %s
+# RUN: env SUPPORTLIB=%mlir_c_runner_utils %PYTHON %s | FileCheck %s
 
 import numpy as np
 import os
 import sys
 
 _SCRIPT_PATH = os.path.dirname(os.path.abspath(__file__))
 sys.path.append(_SCRIPT_PATH)
 from tools import mlir_pytaco_api as pt

mlir/test/Integration/Dialect/SparseTensor/taco/test_tensor_unary_ops.py

-# RUN: SUPPORTLIB=%mlir_lib_dir/libmlir_c_runner_utils%shlibext %PYTHON %s | FileCheck %s
+# RUN: env SUPPORTLIB=%mlir_c_runner_utils %PYTHON %s | FileCheck %s
 
 import numpy as np
 import os
 import sys
 
 _SCRIPT_PATH = os.path.dirname(os.path.abspath(__file__))
 sys.path.append(_SCRIPT_PATH)
 from tools import mlir_pytaco_api as pt

mlir/test/Integration/Dialect/SparseTensor/taco/test_true_dense_tensor_algebra.py

-# RUN: SUPPORTLIB=%mlir_lib_dir/libmlir_c_runner_utils%shlibext %PYTHON %s | FileCheck %s
+# RUN: env SUPPORTLIB=%mlir_c_runner_utils %PYTHON %s | FileCheck %s
 
 import numpy as np
 import os
 import sys
 
 _SCRIPT_PATH = os.path.dirname(os.path.abspath(__file__))
 sys.path.append(_SCRIPT_PATH)
 from tools import mlir_pytaco_api as pt

mlir/test/Integration/Dialect/SparseTensor/taco/unit_test_tensor_core.py

-# RUN: SUPPORTLIB=%mlir_lib_dir/libmlir_c_runner_utils%shlibext %PYTHON %s | FileCheck %s
+# RUN: env SUPPORTLIB=%mlir_c_runner_utils %PYTHON %s | FileCheck %s
 
 from string import Template
 
 import numpy as np
 import os
 import sys
 import tempfile
 

mlir/test/Integration/Dialect/SparseTensor/taco/unit_test_tensor_io.py

-# RUN: SUPPORTLIB=%mlir_lib_dir/libmlir_c_runner_utils%shlibext %PYTHON %s | FileCheck %s
+# RUN: env SUPPORTLIB=%mlir_c_runner_utils %PYTHON %s | FileCheck %s
 
 from string import Template
 
 import numpy as np
 import os
 import sys
 import tempfile
 

mlir/test/Integration/Dialect/SparseTensor/taco/unit_test_tensor_utils.py

-# RUN: SUPPORTLIB=%mlir_lib_dir/libmlir_c_runner_utils%shlibext %PYTHON %s | FileCheck %s
+# RUN: env SUPPORTLIB=%mlir_c_runner_utils %PYTHON %s | FileCheck %s
 
 from typing import Sequence
 import dataclasses
 import numpy as np
 import os
 import sys
 import tempfile
 

mlir/test/Integration/Dialect/Standard/CPU/test-ceil-floor-pos-neg.mlir

 // RUN: mlir-opt %s -pass-pipeline="builtin.module(func.func(convert-vector-to-scf,lower-affine,convert-scf-to-cf,memref-expand,arith-expand),convert-vector-to-llvm,finalize-memref-to-llvm,convert-func-to-llvm,reconcile-unrealized-casts)" | \
 // RUN: mlir-cpu-runner -e entry -entry-point-result=void  \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:   -shared-libs=%mlir_c_runner_utils | \
 // RUN: FileCheck %s
 
 func.func @transfer_read_2d(%A : memref<40xi32>, %base1: index) {
   %i42 = arith.constant -42: i32
   %f = vector.transfer_read %A[%base1], %i42
       {permutation_map = affine_map<(d0) -> (d0)>} :
     memref<40xi32>, vector<40xi32>
   vector.print %f: vector<40xi32>

mlir/test/Integration/Dialect/Standard/CPU/test_subview.mlir

 // RUN: mlir-opt %s -expand-strided-metadata -lower-affine -convert-arith-to-llvm -finalize-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e main -entry-point-result=void \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext | FileCheck %s
+// RUN:   -shared-libs=%mlir_runner_utils | FileCheck %s
 
 memref.global "private" constant @__constant_5x3xf32 : memref<5x3xf32> =
 dense<[[0.0, 1.0, 2.0],
        [3.0, 4.0, 5.0],
        [6.0, 7.0, 8.0],
        [9.0, 10.0, 11.0],
        [12.0, 13.0, 14.0]]>
 

mlir/test/Integration/Dialect/Vector/CPU/AMX/test-mulf-full.mlir

 // RUN: mlir-opt %s -convert-vector-to-scf -lower-affine -convert-scf-to-cf \
 // RUN:  -arith-bufferize -convert-vector-to-llvm="enable-amx" \
 // RUN:  -finalize-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-translate -mlir-to-llvmir | \
 // RUN: %lli --entry-function=entry --mattr="+amx-tile,+amx-int8,+amx-bf16" \
-// RUN:  --dlopen=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:  --dlopen=%mlir_c_runner_utils | \
 // RUN: FileCheck %s
 
 // Note: To run this test, your CPU must support AMX.
 
 // Multiply full size tiles into zero destination.
 func.func @kernel(%arg0: memref<16x32xbf16>,
              %arg1: memref<16x32xbf16>,
              %arg2: memref<16x16xf32>) {

mlir/test/Integration/Dialect/Vector/CPU/AMX/test-mulf.mlir

 // RUN: mlir-opt %s -convert-vector-to-scf -lower-affine -convert-scf-to-cf -convert-vector-to-llvm="enable-amx" -finalize-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-translate -mlir-to-llvmir | \
-// RUN: %lli --entry-function=entry --mattr="+amx-tile,+amx-int8,+amx-bf16" --dlopen=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN: %lli --entry-function=entry --mattr="+amx-tile,+amx-int8,+amx-bf16" --dlopen=%mlir_c_runner_utils | \
 // RUN: FileCheck %s
 
 // Note: To run this test, your CPU must support AMX.
 
 // Multiply into zeroed destination.
 func.func @kernel1(%arg0: memref<2x4xbf16>,
               %arg1: memref<2x4xbf16>,
               %arg2: memref<2x2xf32>) {

mlir/test/Integration/Dialect/Vector/CPU/AMX/test-muli-ext.mlir

 // RUN: mlir-opt %s -convert-vector-to-scf -lower-affine -convert-scf-to-cf -convert-vector-to-llvm="enable-amx" -finalize-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-translate -mlir-to-llvmir | \
-// RUN: %lli --entry-function=entry --mattr="+amx-tile,+amx-int8,+amx-bf16" --dlopen=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN: %lli --entry-function=entry --mattr="+amx-tile,+amx-int8,+amx-bf16" --dlopen=%mlir_c_runner_utils | \
 // RUN: FileCheck %s
 
 // Note: To run this test, your CPU must support AMX.
 
 func.func @print(%arg0: memref<16x4xi32>) {
   %iu = arith.constant -1: i32
   %c0 = arith.constant 0: index
   %c1 = arith.constant 1: index

mlir/test/Integration/Dialect/Vector/CPU/AMX/test-muli-full.mlir

 // RUN: mlir-opt %s -convert-vector-to-scf -lower-affine -convert-scf-to-cf \
 // RUN:  -arith-bufferize -convert-vector-to-llvm="enable-amx" \
 // RUN:  -finalize-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-translate -mlir-to-llvmir | \
 // RUN: %lli --entry-function=entry --mattr="+amx-tile,+amx-int8,+amx-bf16" \
-// RUN:  --dlopen=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:  --dlopen=%mlir_c_runner_utils | \
 // RUN: FileCheck %s
 
 // Note: To run this test, your CPU must support AMX.
 
 // Multiply full size tiles into zero destination.
 func.func @kernel(%arg0: memref<16x64xi8>,
              %arg1: memref<16x64xi8>,
              %arg2: memref<16x16xi32>) {

mlir/test/Integration/Dialect/Vector/CPU/AMX/test-muli.mlir

 // RUN: mlir-opt %s -convert-vector-to-scf -lower-affine -convert-scf-to-cf -convert-vector-to-llvm="enable-amx" -finalize-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-translate -mlir-to-llvmir | \
-// RUN: %lli --entry-function=entry --mattr="+amx-tile,+amx-int8,+amx-bf16" --dlopen=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN: %lli --entry-function=entry --mattr="+amx-tile,+amx-int8,+amx-bf16" --dlopen=%mlir_c_runner_utils | \
 // RUN: FileCheck %s
 
 // Note: To run this test, your CPU must support AMX.
 
 // Multiply into zeroed destination.
 func.func @kernel1(%arg0: memref<2x8xi8>,
               %arg1: memref<2x8xi8>,
               %arg2: memref<2x2xi32>) {

mlir/test/Integration/Dialect/Vector/CPU/AMX/test-tilezero-block.mlir

 // RUN: mlir-opt %s -convert-vector-to-scf -lower-affine -convert-scf-to-cf -convert-vector-to-llvm="enable-amx" -finalize-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-translate -mlir-to-llvmir | \
-// RUN: %lli --entry-function=entry --mattr="+amx-tile,+amx-int8,+amx-bf16" --dlopen=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN: %lli --entry-function=entry --mattr="+amx-tile,+amx-int8,+amx-bf16" --dlopen=%mlir_c_runner_utils | \
 // RUN: FileCheck %s
 
 // Note: To run this test, your CPU must support AMX.
 
 func.func @print(%arg0: memref<4x32xf32>) {
   %fu = arith.constant -1.0: f32
   %c0 = arith.constant 0: index
   %c1 = arith.constant 1: index

mlir/test/Integration/Dialect/Vector/CPU/AMX/test-tilezero.mlir

 // RUN: mlir-opt %s -convert-vector-to-scf -lower-affine -convert-scf-to-cf -convert-vector-to-llvm="enable-amx" -finalize-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-translate -mlir-to-llvmir | \
-// RUN: %lli --entry-function=entry --mattr="+amx-tile,+amx-int8,+amx-bf16" --dlopen=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN: %lli --entry-function=entry --mattr="+amx-tile,+amx-int8,+amx-bf16" --dlopen=%mlir_c_runner_utils | \
 // RUN: FileCheck %s
 
 // Note: To run this test, your CPU must support AMX.
 
 func.func @tilezero(%arg0: memref<?x?xi32>, %i: index, %j: index) {
   %1 = amx.tile_zero : vector<16x16xi32>
   amx.tile_store %arg0[%i, %j], %1 : memref<?x?xi32>, vector<16x16xi32>
   return

mlir/test/Integration/Dialect/Vector/CPU/X86Vector/test-dot.mlir

 // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm="enable-x86vector" -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-translate --mlir-to-llvmir | \
-// RUN: %lli --entry-function=entry --mattr="avx" --dlopen=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN: %lli --entry-function=entry --mattr="avx" --dlopen=%mlir_c_runner_utils | \
 // RUN: FileCheck %s
 
 func.func @entry() -> i32 {
   %i0 = arith.constant 0 : i32
   %i4 = arith.constant 4 : i32
 
   %a = arith.constant dense<[1.0,  2.0,  3.0,  4.0,  5.0,  6.0,  7.0,  8.0]> : vector<8xf32>
   %b = arith.constant dense<[9.0, 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0]> : vector<8xf32>

mlir/test/Integration/Dialect/Vector/CPU/X86Vector/test-inline-asm-vector-avx512.mlir

 // RUN: mlir-opt %s -convert-linalg-to-loops -convert-vector-to-scf='full-unroll=true' -lower-affine -convert-scf-to-cf -convert-vector-to-llvm -finalize-memref-to-llvm  -convert-func-to-llvm='use-bare-ptr-memref-call-conv=1' -convert-arith-to-llvm -reconcile-unrealized-casts |\
 // RUN: mlir-translate --mlir-to-llvmir |\
-// RUN: %lli --entry-function=entry --mattr="avx512f" --dlopen=%mlir_lib_dir/libmlir_c_runner_utils%shlibext |\
+// RUN: %lli --entry-function=entry --mattr="avx512f" --dlopen=%mlir_c_runner_utils |\
 // RUN: FileCheck %s
 
 module {
 
   // an array of 16 i32 of values [0..15]
   llvm.mlir.global private @const16(
     dense<[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15]> : tensor<16 x i32>)
       : !llvm.array<16 x i32>

mlir/test/Integration/Dialect/Vector/CPU/X86Vector/test-mask-compress.mlir

 // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm="enable-x86vector" -convert-func-to-llvm -reconcile-unrealized-casts  | \
 // RUN: mlir-translate  --mlir-to-llvmir | \
-// RUN: %lli --entry-function=entry --mattr="avx512bw" --dlopen=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN: %lli --entry-function=entry --mattr="avx512bw" --dlopen=%mlir_c_runner_utils | \
 // RUN: FileCheck %s
 
 func.func @entry() -> i32 {
   %i0 = arith.constant 0 : i32
 
   %a = arith.constant dense<[1., 0., 0., 2., 4., 3., 5., 7., 8., 1., 5., 5., 3., 1., 0., 7.]> : vector<16xf32>
   %k = arith.constant dense<[1,  0,  1,  1,  1,  0,  0,  0,  0,  0,  1,  1,  1,  1,  1,  0]> : vector<16xi1>
   %r1 = x86vector.avx512.mask.compress %k, %a : vector<16xf32>

mlir/test/Integration/Dialect/Vector/CPU/X86Vector/test-rsqrt.mlir

 // RUN: mlir-opt %s -convert-vector-to-llvm="enable-x86vector" -convert-func-to-llvm | \
 // RUN: mlir-translate --mlir-to-llvmir | \
-// RUN: %lli --entry-function=entry --mattr="avx" --dlopen=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN: %lli --entry-function=entry --mattr="avx" --dlopen=%mlir_c_runner_utils | \
 // RUN: FileCheck %s
 
 func.func @entry() -> i32 {
   %i0 = arith.constant 0 : i32
 
   %v = arith.constant dense<[0.125, 0.25, 0.5, 1.0, 2.0, 4.0, 8.0, 16.0]> : vector<8xf32>
   %r = x86vector.avx.rsqrt %v : vector<8xf32>
   // `rsqrt` may produce slightly different results on Intel and AMD machines: accept both results here.
   // CHECK: {{( 2.82[0-9]*, 1.99[0-9]*, 1.41[0-9]*, 0.99[0-9]*, 0.70[0-9]*, 0.49[0-9]*, 0.35[0-9]*, 0.24[0-9]* )}}
   vector.print %r : vector<8xf32>
 
   return %i0 : i32
 }

mlir/test/Integration/Dialect/Vector/CPU/X86Vector/test-sparse-dot-product.mlir

 // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm="enable-x86vector" -finalize-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts  | \
 // RUN: mlir-translate  --mlir-to-llvmir | \
-// RUN: %lli --entry-function=entry --mattr="avx512bw,avx512vp2intersect" --dlopen=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN: %lli --entry-function=entry --mattr="avx512bw,avx512vp2intersect" --dlopen=%mlir_c_runner_utils | \
 // RUN: FileCheck %s
 
 // This test shows how to implement a sparse vector-vector dot product with
 // AVX512. It uses vp2intersect, mask.compress and vector.contract to compute
 // the dot product of two sparse HW vectors of 8 float64 elements ("segment").
 // Each sparse vector is represented by an index memref (A or C) and by a data
 // memref (B or D), containing M or N elements.
 //

mlir/test/Integration/Dialect/Vector/CPU/X86Vector/test-vp2intersect-i32.mlir

 // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm="enable-x86vector" -convert-func-to-llvm -reconcile-unrealized-casts  | \
 // RUN: mlir-translate  --mlir-to-llvmir | \
-// RUN: %lli --entry-function=entry --mattr="avx512bw,avx512vp2intersect" --dlopen=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN: %lli --entry-function=entry --mattr="avx512bw,avx512vp2intersect" --dlopen=%mlir_c_runner_utils | \
 // RUN: FileCheck %s
 
 // Note: To run this test, your CPU must support AVX512 vp2intersect.
 
 func.func @entry() -> i32 {
   %i0 = arith.constant 0 : i32
   %i1 = arith.constant 1: i32
   %i2 = arith.constant 2: i32

mlir/test/Integration/Dialect/Vector/CPU/lit.local.cfg

-import sys
-
-# No JIT on win32.
-if sys.platform == 'win32':
-    config.unsupported = True

mlir/test/Integration/Dialect/Vector/CPU/test-0-d-vectors.mlir

 // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -finalize-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:   -shared-libs=%mlir_c_runner_utils | \
 // RUN: FileCheck %s
 
 func.func @extract_element_0d(%a: vector<f32>) {
   %1 = vector.extractelement %a[] : vector<f32>
   // CHECK: 42
   vector.print %1: f32
   return
 }

mlir/test/Integration/Dialect/Vector/CPU/test-broadcast.mlir

 // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e entry -entry-point-result=void  \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:   -shared-libs=%mlir_c_runner_utils | \
 // RUN: FileCheck %s
 
 func.func @entry() {
   %i = arith.constant 2147483647: i32
   %l = arith.constant 9223372036854775807 : i64
 
   %f0 = arith.constant 0.0: f32
   %f1 = arith.constant 1.0: f32

mlir/test/Integration/Dialect/Vector/CPU/test-compress.mlir

 // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -finalize-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:   -shared-libs=%mlir_c_runner_utils | \
 // RUN: FileCheck %s
 
 func.func @compress16(%base: memref<?xf32>,
                  %mask: vector<16xi1>, %value: vector<16xf32>) {
   %c0 = arith.constant 0: index
   vector.compressstore %base[%c0], %mask, %value
     : memref<?xf32>, vector<16xi1>, vector<16xf32>
   return

mlir/test/Integration/Dialect/Vector/CPU/test-constant-mask.mlir

 // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e entry -entry-point-result=void  \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:   -shared-libs=%mlir_c_runner_utils | \
 // RUN: FileCheck %s
 
 func.func @entry() {
   %0 = vector.constant_mask [4] : vector<8xi1>
   vector.print %0 : vector<8xi1>
   // CHECK: ( 1, 1, 1, 1, 0, 0, 0, 0 )
 
   %1 = vector.constant_mask [1, 3] : vector<4x4xi1>

mlir/test/Integration/Dialect/Vector/CPU/test-contraction.mlir

 // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e entry -entry-point-result=void  \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:   -shared-libs=%mlir_c_runner_utils | \
 // RUN: FileCheck %s
 
 #dotp_accesses = [
   affine_map<(i) -> (i)>,
   affine_map<(i) -> (i)>,
   affine_map<(i) -> ()>
 ]
 #dotp_trait = {

mlir/test/Integration/Dialect/Vector/CPU/test-create-mask-v4i1.mlir

 // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e entry -entry-point-result=void  \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:   -shared-libs=%mlir_c_runner_utils | \
 // RUN: FileCheck %s
 
 // NOTE: This is similar to test-create-mask.mlir, but with a different length,
 //       because the v4i1 vector specifically exposed bugs in the LLVM backend.
 
 func.func @entry() {
   %c0 = arith.constant 0 : index
   %c1 = arith.constant 1 : index

mlir/test/Integration/Dialect/Vector/CPU/test-create-mask.mlir

 // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e entry -entry-point-result=void  \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:   -shared-libs=%mlir_c_runner_utils | \
 // RUN: FileCheck %s
 
 func.func @entry() {
   %cneg1 = arith.constant -1 : index
   %c0 = arith.constant 0 : index
   %c1 = arith.constant 1 : index
   %c2 = arith.constant 2 : index
   %c3 = arith.constant 3 : index

mlir/test/Integration/Dialect/Vector/CPU/test-expand.mlir

 // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -finalize-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:   -shared-libs=%mlir_c_runner_utils | \
 // RUN: FileCheck %s
 
 func.func @expand16(%base: memref<?xf32>,
                %mask: vector<16xi1>,
                %pass_thru: vector<16xf32>) -> vector<16xf32> {
   %c0 = arith.constant 0: index
   %e = vector.expandload %base[%c0], %mask, %pass_thru
     : memref<?xf32>, vector<16xi1>, vector<16xf32> into vector<16xf32>

mlir/test/Integration/Dialect/Vector/CPU/test-extract-strided-slice.mlir

 // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e entry -entry-point-result=void  \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:   -shared-libs=%mlir_c_runner_utils | \
 // RUN: FileCheck %s
 
 func.func @entry() {
   %f0 = arith.constant 0.0: f32
   %f1 = arith.constant 1.0: f32
   %f2 = arith.constant 2.0: f32
   %f3 = arith.constant 3.0: f32
   %f4 = arith.constant 4.0: f32

mlir/test/Integration/Dialect/Vector/CPU/test-flat-transpose-col.mlir

 // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e entry -entry-point-result=void  \
 // RUN:   -O0 -enable-matrix -matrix-allow-contract -matrix-default-layout=column-major \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:   -shared-libs=%mlir_c_runner_utils | \
 // RUN: FileCheck %s
 
 func.func @entry() {
   %f0 = arith.constant 0.0: f64
   %f1 = arith.constant 1.0: f64
   %f2 = arith.constant 2.0: f64
   %f3 = arith.constant 3.0: f64
   %f4 = arith.constant 4.0: f64

mlir/test/Integration/Dialect/Vector/CPU/test-flat-transpose-row.mlir

 // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e entry -entry-point-result=void  \
 // RUN:   -O0 -enable-matrix -matrix-allow-contract -matrix-default-layout=row-major \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:   -shared-libs=%mlir_c_runner_utils | \
 // RUN: FileCheck %s
 
 func.func @entry() {
   %f0 = arith.constant 0.0: f64
   %f1 = arith.constant 1.0: f64
   %f2 = arith.constant 2.0: f64
   %f3 = arith.constant 3.0: f64
   %f4 = arith.constant 4.0: f64

mlir/test/Integration/Dialect/Vector/CPU/test-fma.mlir

 // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e entry -entry-point-result=void  \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:   -shared-libs=%mlir_c_runner_utils | \
 // RUN: FileCheck %s
 
 func.func @entry() {
   %f1 = arith.constant 1.0: f32
   %f3 = arith.constant 3.0: f32
   %f7 = arith.constant 7.0: f32
   %v1 = vector.broadcast %f1 : f32 to vector<8xf32>
   %v3 = vector.broadcast %f3 : f32 to vector<8xf32>

mlir/test/Integration/Dialect/Vector/CPU/test-gather.mlir

 // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -finalize-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:   -shared-libs=%mlir_c_runner_utils | \
 // RUN: FileCheck %s
 
 func.func @gather8(%base: memref<?xf32>, %indices: vector<8xi32>,
               %mask: vector<8xi1>, %pass_thru: vector<8xf32>) -> vector<8xf32> {
   %c0 = arith.constant 0: index
   %g = vector.gather %base[%c0][%indices], %mask, %pass_thru
     : memref<?xf32>, vector<8xi32>, vector<8xi1>, vector<8xf32> into vector<8xf32>
   return %g : vector<8xf32>

mlir/test/Integration/Dialect/Vector/CPU/test-index-vectors.mlir

 // RUN: mlir-opt %s -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e entry -entry-point-result=void  \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:   -shared-libs=%mlir_c_runner_utils | \
 // RUN: FileCheck %s
 
 func.func @entry() {
   %c0 = arith.constant dense<[0, 1, 2, 3]>: vector<4xindex>
   %c1 = arith.constant dense<[0, 1]>: vector<2xindex>
   %c2 = arith.constant 2 : index
 
   %v1 = vector.broadcast %c0 : vector<4xindex> to vector<2x4xindex>

mlir/test/Integration/Dialect/Vector/CPU/test-insert-strided-slice.mlir

 // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e entry -entry-point-result=void  \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:   -shared-libs=%mlir_c_runner_utils | \
 // RUN: FileCheck %s
 
 func.func @entry() {
   %f1 = arith.constant 1.0: f32
   %f2 = arith.constant 2.0: f32
   %f3 = arith.constant 3.0: f32
   %f4 = arith.constant 4.0: f32
   %v1 = vector.broadcast %f1 : f32 to vector<4xf32>

mlir/test/Integration/Dialect/Vector/CPU/test-maskedload.mlir

 // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -finalize-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:   -shared-libs=%mlir_c_runner_utils | \
 // RUN: FileCheck %s
 
 func.func @maskedload16(%base: memref<?xf32>, %mask: vector<16xi1>,
                    %pass_thru: vector<16xf32>) -> vector<16xf32> {
   %c0 = arith.constant 0: index
   %ld = vector.maskedload %base[%c0], %mask, %pass_thru
     : memref<?xf32>, vector<16xi1>, vector<16xf32> into vector<16xf32>
   return %ld : vector<16xf32>

mlir/test/Integration/Dialect/Vector/CPU/test-maskedstore.mlir

 // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -finalize-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:   -shared-libs=%mlir_c_runner_utils | \
 // RUN: FileCheck %s
 
 func.func @maskedstore16(%base: memref<?xf32>,
                     %mask: vector<16xi1>, %value: vector<16xf32>) {
   %c0 = arith.constant 0: index
   vector.maskedstore %base[%c0], %mask, %value
     : memref<?xf32>, vector<16xi1>, vector<16xf32>
   return

mlir/test/Integration/Dialect/Vector/CPU/test-matrix-multiply-col.mlir

 // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e entry -entry-point-result=void  \
 // RUN:   -O0 -enable-matrix -matrix-allow-contract -matrix-default-layout=column-major \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:   -shared-libs=%mlir_c_runner_utils | \
 // RUN: FileCheck %s
 
 func.func @entry() {
   %f0 = arith.constant 0.0: f64
   %f1 = arith.constant 1.0: f64
   %f2 = arith.constant 2.0: f64
   %f3 = arith.constant 3.0: f64
   %f4 = arith.constant 4.0: f64

mlir/test/Integration/Dialect/Vector/CPU/test-matrix-multiply-row.mlir

 // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e entry -entry-point-result=void  \
 // RUN:   -O0 -enable-matrix -matrix-allow-contract -matrix-default-layout=row-major \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:   -shared-libs=%mlir_c_runner_utils | \
 // RUN: FileCheck %s
 
 func.func @entry() {
   %f0 = arith.constant 0.0: f64
   %f1 = arith.constant 1.0: f64
   %f2 = arith.constant 2.0: f64
   %f3 = arith.constant 3.0: f64
   %f4 = arith.constant 4.0: f64

mlir/test/Integration/Dialect/Vector/CPU/test-outerproduct-f32.mlir

 // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e entry -entry-point-result=void  \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:   -shared-libs=%mlir_c_runner_utils | \
 // RUN: FileCheck %s
 
 !vector_type_A = vector<8xf32>
 !vector_type_B = vector<8xf32>
 !vector_type_C = vector<8x8xf32>
 
 !vector_type_X = vector<2xf32>
 !vector_type_Y = vector<3xf32>

mlir/test/Integration/Dialect/Vector/CPU/test-outerproduct-i64.mlir

 // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e entry -entry-point-result=void  \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:   -shared-libs=%mlir_c_runner_utils | \
 // RUN: FileCheck %s
 
 !vector_type_A = vector<8xi64>
 !vector_type_B = vector<8xi64>
 !vector_type_C = vector<8x8xi64>
 
 !vector_type_X = vector<2xi64>
 !vector_type_Y = vector<3xi64>

mlir/test/Integration/Dialect/Vector/CPU/test-print-int.mlir

 // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e entry -entry-point-result=void  \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:   -shared-libs=%mlir_c_runner_utils | \
 // RUN: FileCheck %s
 
 //
 // Test various signless, signed, unsigned integer types.
 //
 func.func @entry() {
   %0 = arith.constant dense<[true, false, -1, 0, 1]> : vector<5xi1>
   vector.print %0 : vector<5xi1>

mlir/test/Integration/Dialect/Vector/CPU/test-realloc.mlir

 // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -finalize-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts |\
 // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext
+// RUN:   -shared-libs=%mlir_c_runner_utils
 // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -finalize-memref-to-llvm='use-aligned-alloc=1' -convert-func-to-llvm -arith-expand -reconcile-unrealized-casts |\
 // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | FileCheck %s
+// RUN:   -shared-libs=%mlir_c_runner_utils | FileCheck %s
+
+// FIXME: Windows does not have aligned_alloc
+// UNSUPPORTED: system-windows
 
 func.func @entry() {
   // Set up memory.
   %c0 = arith.constant 0: index
   %c1 = arith.constant 1: index
   %c8 = arith.constant 8: index
   %A = memref.alloc() : memref<8xf32>
   scf.for %i = %c0 to %c8 step %c1 {

mlir/test/Integration/Dialect/Vector/CPU/test-reductions-f32-reassoc.mlir

 // RUN: mlir-opt %s -convert-scf-to-cf \
 // RUN:             -convert-vector-to-llvm='reassociate-fp-reductions' \
 // RUN:             -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e entry -entry-point-result=void  \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:   -shared-libs=%mlir_c_runner_utils | \
 // RUN: FileCheck %s
 
 func.func @entry() {
   // Construct test vector, numerically very stable.
   %f1 = arith.constant 1.0: f32
   %f2 = arith.constant 2.0: f32
   %f3 = arith.constant 3.0: f32
   %v0 = vector.broadcast %f1 : f32 to vector<64xf32>

mlir/test/Integration/Dialect/Vector/CPU/test-reductions-f32.mlir

 // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e entry -entry-point-result=void  \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:   -shared-libs=%mlir_c_runner_utils | \
 // RUN: FileCheck %s
 
 func.func @entry() {
   // Construct test vector.
   %f1 = arith.constant 1.5: f32
   %f2 = arith.constant 2.0: f32
   %f3 = arith.constant 3.0: f32
   %f4 = arith.constant 4.0: f32

mlir/test/Integration/Dialect/Vector/CPU/test-reductions-f64-reassoc.mlir

 // RUN: mlir-opt %s -convert-scf-to-cf \
 // RUN:             -convert-vector-to-llvm='reassociate-fp-reductions' \
 // RUN:             -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e entry -entry-point-result=void  \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:   -shared-libs=%mlir_c_runner_utils | \
 // RUN: FileCheck %s
 
 func.func @entry() {
   // Construct test vector, numerically very stable.
   %f1 = arith.constant 1.0: f64
   %f2 = arith.constant 2.0: f64
   %f3 = arith.constant 3.0: f64
   %v0 = vector.broadcast %f1 : f64 to vector<64xf64>

mlir/test/Integration/Dialect/Vector/CPU/test-reductions-f64.mlir

 // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e entry -entry-point-result=void  \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:   -shared-libs=%mlir_c_runner_utils | \
 // RUN: FileCheck %s
 
 func.func @entry() {
   // Construct test vector.
   %f1 = arith.constant 1.5: f64
   %f2 = arith.constant 2.0: f64
   %f3 = arith.constant 3.0: f64
   %f4 = arith.constant 4.0: f64

mlir/test/Integration/Dialect/Vector/CPU/test-reductions-i32.mlir

 // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e entry -entry-point-result=void  \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:   -shared-libs=%mlir_c_runner_utils | \
 // RUN: FileCheck %s
 
 func.func @entry() {
   // Construct test vector.
   %i1 = arith.constant 1: i32
   %i2 = arith.constant 2: i32
   %i3 = arith.constant 3: i32
   %i4 = arith.constant 4: i32

mlir/test/Integration/Dialect/Vector/CPU/test-reductions-i4.mlir

 // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e entry -entry-point-result=void  \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:   -shared-libs=%mlir_c_runner_utils | \
 // RUN: FileCheck %s
 
 func.func @entry() {
   %v = arith.constant dense<[-8, -7, -6, -5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15]> : vector<24xi4>
   vector.print %v : vector<24xi4>
   //
   // Test vector:
   //

mlir/test/Integration/Dialect/Vector/CPU/test-reductions-i64.mlir

 // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e entry -entry-point-result=void  \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:   -shared-libs=%mlir_c_runner_utils | \
 // RUN: FileCheck %s
 
 func.func @entry() {
   // Construct test vector.
   %i1 = arith.constant 1: i64
   %i2 = arith.constant 2: i64
   %i3 = arith.constant 3: i64
   %i4 = arith.constant 4: i64

mlir/test/Integration/Dialect/Vector/CPU/test-reductions-si4.mlir

 // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e entry -entry-point-result=void  \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:   -shared-libs=%mlir_c_runner_utils | \
 // RUN: FileCheck %s
 
 func.func @entry() {
   %v0 = arith.constant dense<[-8, -7, -6, -5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5, 6, 7]> : vector<16xi4>
   %v = vector.bitcast %v0 : vector<16xi4> to vector<16xsi4>
   vector.print %v : vector<16xsi4>
   //
   // Test vector:

mlir/test/Integration/Dialect/Vector/CPU/test-reductions-ui4.mlir

 // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e entry -entry-point-result=void  \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:   -shared-libs=%mlir_c_runner_utils | \
 // RUN: FileCheck %s
 
 func.func @entry() {
   %v0 = arith.constant dense<[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15]> : vector<16xi4>
   %v = vector.bitcast %v0 : vector<16xi4> to vector<16xui4>
   vector.print %v : vector<16xui4>
   //
   // Test vector:

mlir/test/Integration/Dialect/Vector/CPU/test-scan.mlir

 // RUN: mlir-opt %s -test-vector-scan-lowering -convert-scf-to-cf -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e entry -entry-point-result=void  \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:   -shared-libs=%mlir_c_runner_utils | \
 // RUN: FileCheck %s
 
 func.func @entry() {
   %f1 = arith.constant 1.0: f32
   %f2 = arith.constant 2.0: f32
   %f3 = arith.constant 3.0: f32
   %f4 = arith.constant 4.0: f32
   %f5 = arith.constant 5.0: f32

mlir/test/Integration/Dialect/Vector/CPU/test-scatter.mlir

 // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -finalize-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:   -shared-libs=%mlir_c_runner_utils | \
 // RUN: FileCheck %s
 
 func.func @scatter8(%base: memref<?xf32>,
                %indices: vector<8xi32>,
                %mask: vector<8xi1>, %value: vector<8xf32>) {
   %c0 = arith.constant 0: index
   vector.scatter %base[%c0][%indices], %mask, %value
     : memref<?xf32>, vector<8xi32>, vector<8xi1>, vector<8xf32>

mlir/test/Integration/Dialect/Vector/CPU/test-shape-cast.mlir

 // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e entry -entry-point-result=void  \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:   -shared-libs=%mlir_c_runner_utils | \
 // RUN: FileCheck %s
 
 func.func @entry() {
   %f1 = arith.constant 1.0: f32
   %f2 = arith.constant 2.0: f32
   %f3 = arith.constant 3.0: f32
   %f4 = arith.constant 4.0: f32
   %f5 = arith.constant 5.0: f32

mlir/test/Integration/Dialect/Vector/CPU/test-shuffle.mlir

 // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e entry -entry-point-result=void  \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:   -shared-libs=%mlir_c_runner_utils | \
 // RUN: FileCheck %s
 
 func.func @entry() {
   %f1 = arith.constant 1.0: f32
   %f2 = arith.constant 2.0: f32
   %v1 = vector.broadcast %f1 : f32 to vector<2x4xf32>
   %v2 = vector.broadcast %f2 : f32 to vector<2x4xf32>
   vector.print %v1 : vector<2x4xf32>

mlir/test/Integration/Dialect/Vector/CPU/test-sparse-dot-matvec.mlir

 // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -finalize-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:   -shared-libs=%mlir_c_runner_utils | \
 // RUN: FileCheck %s
 
 // Illustrates an 8x8 Sparse Matrix x Vector implemented with only operations
 // of the vector dialect (and some std/scf). Essentially, this example performs
 // the following multiplication:
 //
 //     0  1  2  3  4  5  6  7
 //   +------------------------+

mlir/test/Integration/Dialect/Vector/CPU/test-sparse-saxpy-jagged-matvec.mlir

 // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -finalize-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e entry -entry-point-result=void \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:   -shared-libs=%mlir_c_runner_utils | \
 // RUN: FileCheck %s
 
 // Illustrates an 8x8 Sparse Matrix x Vector implemented with only operations
 // of the vector dialect (and some std/scf). Essentially, this example performs
 // the following multiplication:
 //
 //     0  1  2  3  4  5  6  7
 //   +------------------------+

mlir/test/Integration/Dialect/Vector/CPU/test-transfer-read-1d.mlir

 // RUN: mlir-opt %s -pass-pipeline="builtin.module(func.func(convert-vector-to-scf,expand-strided-metadata,lower-affine,convert-arith-to-llvm,convert-scf-to-cf),convert-vector-to-llvm,finalize-memref-to-llvm,convert-func-to-llvm,reconcile-unrealized-casts)" | \
 // RUN: mlir-cpu-runner -e entry -entry-point-result=void  \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:   -shared-libs=%mlir_c_runner_utils | \
 // RUN: FileCheck %s
 
 // RUN: mlir-opt %s -pass-pipeline="builtin.module(func.func(convert-vector-to-scf{full-unroll=true},expand-strided-metadata,lower-affine,convert-arith-to-llvm,convert-scf-to-cf),convert-vector-to-llvm,finalize-memref-to-llvm,convert-func-to-llvm,reconcile-unrealized-casts)" | \
 // RUN: mlir-cpu-runner -e entry -entry-point-result=void  \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:   -shared-libs=%mlir_c_runner_utils | \
 // RUN: FileCheck %s
 
 // Test for special cases of 1D vector transfer ops.
 
 memref.global "private" @gv : memref<5x6xf32> =
     dense<[[0. , 1. , 2. , 3. , 4. , 5. ],
            [10., 11., 12., 13., 14., 15.],
            [20., 21., 22., 23., 24., 25.],

mlir/test/Integration/Dialect/Vector/CPU/test-transfer-read-2d.mlir

 // RUN: mlir-opt %s -pass-pipeline="builtin.module(func.func(convert-vector-to-scf,lower-affine,convert-scf-to-cf),convert-vector-to-llvm,finalize-memref-to-llvm,convert-func-to-llvm,reconcile-unrealized-casts)" | \
 // RUN: mlir-cpu-runner -e entry -entry-point-result=void  \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:   -shared-libs=%mlir_c_runner_utils | \
 // RUN: FileCheck %s
 
 // RUN: mlir-opt %s -pass-pipeline="builtin.module(func.func(convert-vector-to-scf{full-unroll=true},lower-affine,convert-scf-to-cf),convert-vector-to-llvm,finalize-memref-to-llvm,convert-func-to-llvm,reconcile-unrealized-casts)" | \
 // RUN: mlir-cpu-runner -e entry -entry-point-result=void  \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:   -shared-libs=%mlir_c_runner_utils | \
 // RUN: FileCheck %s
 
 memref.global "private" @gv : memref<3x4xf32> = dense<[[0. , 1. , 2. , 3. ],
                                                        [10., 11., 12., 13.],
                                                        [20., 21., 22., 23.]]>
 
 // Vector load.
 func.func @transfer_read_2d(%A : memref<?x?xf32>, %base1: index, %base2: index) {

mlir/test/Integration/Dialect/Vector/CPU/test-transfer-read-3d.mlir

 // RUN: mlir-opt %s -pass-pipeline="builtin.module(func.func(convert-vector-to-scf,lower-affine,convert-scf-to-cf),convert-vector-to-llvm,finalize-memref-to-llvm,convert-func-to-llvm,reconcile-unrealized-casts)" | \
 // RUN: mlir-cpu-runner -e entry -entry-point-result=void  \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:   -shared-libs=%mlir_c_runner_utils | \
 // RUN: FileCheck %s
 
 // RUN: mlir-opt %s -pass-pipeline="builtin.module(func.func(convert-vector-to-scf{full-unroll=true},lower-affine,convert-scf-to-cf),convert-vector-to-llvm,finalize-memref-to-llvm,convert-func-to-llvm,reconcile-unrealized-casts)" | \
 // RUN: mlir-cpu-runner -e entry -entry-point-result=void  \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:   -shared-libs=%mlir_c_runner_utils | \
 // RUN: FileCheck %s
 
 func.func @transfer_read_3d(%A : memref<?x?x?x?xf32>,
                        %o: index, %a: index, %b: index, %c: index) {
   %fm42 = arith.constant -42.0: f32
   %f = vector.transfer_read %A[%o, %a, %b, %c], %fm42
       : memref<?x?x?x?xf32>, vector<2x5x3xf32>
   vector.print %f: vector<2x5x3xf32>

mlir/test/Integration/Dialect/Vector/CPU/test-transfer-read.mlir

 // RUN: mlir-opt %s -pass-pipeline="builtin.module(func.func(convert-vector-to-scf,lower-affine,convert-scf-to-cf),convert-vector-to-llvm,finalize-memref-to-llvm,convert-func-to-llvm,reconcile-unrealized-casts)" | \
 // RUN: mlir-cpu-runner -e entry -entry-point-result=void  \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:   -shared-libs=%mlir_c_runner_utils | \
 // RUN: FileCheck %s
 
 // RUN: mlir-opt %s -pass-pipeline="builtin.module(func.func(convert-vector-to-scf{full-unroll=true},lower-affine,convert-scf-to-cf),convert-vector-to-llvm,finalize-memref-to-llvm,convert-func-to-llvm,reconcile-unrealized-casts)" | \
 // RUN: mlir-cpu-runner -e entry -entry-point-result=void  \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:   -shared-libs=%mlir_c_runner_utils | \
 // RUN: FileCheck %s
 
 func.func @transfer_read_1d(%A : memref<?xf32>, %base: index) {
   %fm42 = arith.constant -42.0: f32
   %f = vector.transfer_read %A[%base], %fm42
       {permutation_map = affine_map<(d0) -> (d0)>} :
     memref<?xf32>, vector<13xf32>
   vector.print %f: vector<13xf32>

mlir/test/Integration/Dialect/Vector/CPU/test-transfer-to-loops.mlir

 // RUN: mlir-opt %s -pass-pipeline="builtin.module(func.func(convert-vector-to-scf,lower-affine,convert-scf-to-cf),convert-vector-to-llvm,finalize-memref-to-llvm,convert-func-to-llvm,reconcile-unrealized-casts)" | \
 // RUN: mlir-cpu-runner -e main -entry-point-result=void  \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext,%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:   -shared-libs=%mlir_runner_utils,%mlir_c_runner_utils | \
 // RUN: FileCheck %s
 
 // RUN: mlir-opt %s -pass-pipeline="builtin.module(func.func(convert-vector-to-scf{full-unroll=true},lower-affine,convert-scf-to-cf),convert-vector-to-llvm,finalize-memref-to-llvm,convert-func-to-llvm,reconcile-unrealized-casts)" | \
 // RUN: mlir-cpu-runner -e main -entry-point-result=void  \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext,%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:   -shared-libs=%mlir_runner_utils,%mlir_c_runner_utils | \
 // RUN: FileCheck %s
 
 #map0 = affine_map<(d0, d1) -> (d1, d0)>
 #map1 = affine_map<(d0, d1) -> (d1)>
 
 func.func private @printMemrefF32(memref<*xf32>)
 
 func.func @alloc_2d_filled_f32(%arg0: index, %arg1: index) -> memref<?x?xf32> {

mlir/test/Integration/Dialect/Vector/CPU/test-transfer-write.mlir

 // RUN: mlir-opt %s -convert-vector-to-scf -convert-scf-to-cf -convert-vector-to-llvm -finalize-memref-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e entry -entry-point-result=void  \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:   -shared-libs=%mlir_c_runner_utils | \
 // RUN: FileCheck %s
 
 func.func @transfer_write16_inbounds_1d(%A : memref<?xf32>, %base: index) {
   %f = arith.constant 16.0 : f32
   %v = vector.splat %f : vector<16xf32>
   vector.transfer_write %v, %A[%base]
     {permutation_map = affine_map<(d0) -> (d0)>, in_bounds = [true]}
     : vector<16xf32>, memref<?xf32>

mlir/test/Integration/Dialect/Vector/CPU/test-transpose.mlir

 // RUN: mlir-opt %s -convert-scf-to-cf -convert-vector-to-llvm -convert-func-to-llvm -reconcile-unrealized-casts | \
 // RUN: mlir-cpu-runner -e entry -entry-point-result=void  \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | \
+// RUN:   -shared-libs=%mlir_c_runner_utils | \
 // RUN: FileCheck %s
 
 func.func @entry() {
   %f0 = arith.constant 0.0: f32
   %f1 = arith.constant 1.0: f32
   %f2 = arith.constant 2.0: f32
   %f3 = arith.constant 3.0: f32
   %f4 = arith.constant 4.0: f32

mlir/test/Integration/Dialect/Vector/GPU/CUDA/test-reduction-distribute.mlir

 // RUN: mlir-opt %s -test-vector-warp-distribute="hoist-uniform distribute-transfer-write propagate-distribution" -canonicalize |\
 // RUN: mlir-opt -test-vector-warp-distribute=rewrite-warp-ops-to-scf-if |\
 // RUN: mlir-opt  -lower-affine -convert-scf-to-cf -convert-vector-to-llvm \
 // RUN:  -convert-arith-to-llvm -gpu-kernel-outlining |\
 // RUN: mlir-opt -pass-pipeline='builtin.module(gpu.module(strip-debuginfo,convert-gpu-to-nvvm,reconcile-unrealized-casts,gpu-to-cubin))' |\
 // RUN: mlir-opt -gpu-to-llvm -reconcile-unrealized-casts |\
 // RUN: mlir-cpu-runner -e main -entry-point-result=void \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_cuda_runtime%shlibext \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext | \
+// RUN:   -shared-libs=%mlir_cuda_runtime \
+// RUN:   -shared-libs=%mlir_c_runner_utils \
+// RUN:   -shared-libs=%mlir_runner_utils | \
 // RUN: FileCheck %s
 
 // Run a tiled reduction fused with an elementwise op.
 
 func.func @gpu_func(%in: memref<1024xf32>, %out: memref<1xf32>) {
   %c1 = arith.constant 1 : index
   %cst = arith.constant dense<100.0000> : vector<1xf32>
   %cst_0 = arith.constant 0.000000e+00 : f32

mlir/test/Integration/Dialect/Vector/GPU/CUDA/test-warp-distribute.mlir

 // Run the test cases without distributing ops to test default lowering. Run
 // everything on the same thread.
 // RUN: mlir-opt %s -test-vector-warp-distribute=rewrite-warp-ops-to-scf-if -canonicalize | \
 // RUN: mlir-opt -convert-scf-to-cf -convert-cf-to-llvm -convert-vector-to-llvm -convert-arith-to-llvm \
 // RUN:  -gpu-kernel-outlining |\
 // RUN: mlir-opt -pass-pipeline='builtin.module(gpu.module(strip-debuginfo,convert-gpu-to-nvvm,reconcile-unrealized-casts,gpu-to-cubin))' |\
 // RUN: mlir-opt -gpu-to-llvm -reconcile-unrealized-casts |\
 // RUN: mlir-cpu-runner -e main -entry-point-result=void \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_cuda_runtime%shlibext \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext | \
+// RUN:   -shared-libs=%mlir_cuda_runtime \
+// RUN:   -shared-libs=%mlir_c_runner_utils \
+// RUN:   -shared-libs=%mlir_runner_utils | \
 // RUN: FileCheck %s
 
 // Run the same test cases with distribution and propagation.
 // RUN: mlir-opt %s  -test-vector-warp-distribute="hoist-uniform distribute-transfer-write" \
 // RUN:   -test-vector-warp-distribute=rewrite-warp-ops-to-scf-if -canonicalize | \
 // RUN: mlir-opt -convert-scf-to-cf -convert-cf-to-llvm -convert-vector-to-llvm -convert-arith-to-llvm \
 // RUN:  -gpu-kernel-outlining |\
 // RUN: mlir-opt -pass-pipeline='builtin.module(gpu.module(strip-debuginfo,convert-gpu-to-nvvm,reconcile-unrealized-casts,gpu-to-cubin))' |\
 // RUN: mlir-opt -gpu-to-llvm -reconcile-unrealized-casts |\
 // RUN: mlir-cpu-runner -e main -entry-point-result=void \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_cuda_runtime%shlibext \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext | \
+// RUN:   -shared-libs=%mlir_cuda_runtime \
+// RUN:   -shared-libs=%mlir_c_runner_utils \
+// RUN:   -shared-libs=%mlir_runner_utils | \
 // RUN: FileCheck %s
 
 // RUN: mlir-opt %s  -test-vector-warp-distribute="hoist-uniform distribute-transfer-write propagate-distribution" \
 // RUN:   -test-vector-warp-distribute=rewrite-warp-ops-to-scf-if -canonicalize | \
 // RUN: mlir-opt -convert-scf-to-cf -convert-cf-to-llvm -convert-vector-to-llvm -convert-arith-to-llvm \
 // RUN:  -gpu-kernel-outlining |\
 // RUN: mlir-opt -pass-pipeline='builtin.module(gpu.module(strip-debuginfo,convert-gpu-to-nvvm,reconcile-unrealized-casts,gpu-to-cubin))' |\
 // RUN: mlir-opt -gpu-to-llvm -reconcile-unrealized-casts |\
 // RUN: mlir-cpu-runner -e main -entry-point-result=void \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_cuda_runtime%shlibext \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext | \
+// RUN:   -shared-libs=%mlir_cuda_runtime \
+// RUN:   -shared-libs=%mlir_c_runner_utils \
+// RUN:   -shared-libs=%mlir_runner_utils | \
 // RUN: FileCheck %s
 
 func.func @gpu_func(%arg1: memref<32xf32>, %arg2: memref<32xf32>) {
   %c1 = arith.constant 1 : index
   %c0 = arith.constant 0 : index
   %c32 = arith.constant 32 : index
   %cst = arith.constant 0.000000e+00 : f32
   gpu.launch blocks(%arg3, %arg4, %arg5)

mlir/test/Integration/GPU/CUDA/TensorCore/wmma-matmul-f16.mlir

 // RUN: mlir-opt %s \
 // RUN: | mlir-opt -gpu-kernel-outlining \
 // RUN: | mlir-opt -pass-pipeline='builtin.module(gpu.module(strip-debuginfo,convert-gpu-to-nvvm,gpu-to-cubin{chip=sm_70}))' \
 // RUN: | mlir-opt --convert-scf-to-cf -gpu-to-llvm \
 // RUN: | mlir-cpu-runner \
-// RUN:   --shared-libs=%mlir_lib_dir/libmlir_cuda_runtime%shlibext \
-// RUN:   --shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext \
+// RUN:   --shared-libs=%mlir_cuda_runtime \
+// RUN:   --shared-libs=%mlir_runner_utils \
 // RUN:   --entry-point-result=void \
 // RUN: | FileCheck %s
 // Test case to check the working of Tensor cores on Nvidia GPUs. The kernel has already
 // been outlined to prevent crashing due to introduction of an empty basic block by --gpu-
 // kernel-outling.
 func.func @main() {
   %0 = memref.alloc() : memref<16x16xf16>
   %22 = memref.alloc() : memref<16x16xf16>

mlir/test/Integration/GPU/CUDA/TensorCore/wmma-matmul-f32.mlir

 // RUN: mlir-opt %s \
 // RUN: | mlir-opt -gpu-kernel-outlining \
 // RUN: | mlir-opt -pass-pipeline='builtin.module(gpu.module(strip-debuginfo,convert-gpu-to-nvvm,gpu-to-cubin{chip=sm_70}))' \
 // RUN: | mlir-opt --convert-scf-to-cf -gpu-to-llvm \
 // RUN: | mlir-cpu-runner \
-// RUN:   --shared-libs=%mlir_lib_dir/libmlir_cuda_runtime%shlibext \
-// RUN:   --shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext \
+// RUN:   --shared-libs=%mlir_cuda_runtime \
+// RUN:   --shared-libs=%mlir_runner_utils \
 // RUN:   --entry-point-result=void \
 // RUN: | FileCheck %s
 
 func.func @main() {
   %0 = memref.alloc() : memref<16x16xf16>
   %22 = memref.alloc() : memref<16x16xf32>
   %1 = memref.alloc() : memref<16x16xf32>
 

mlir/test/Integration/GPU/CUDA/all-reduce-and.mlir

 // RUN: mlir-opt %s \
 // RUN: | mlir-opt -gpu-kernel-outlining \
 // RUN: | mlir-opt -pass-pipeline='builtin.module(gpu.module(strip-debuginfo,convert-gpu-to-nvvm,gpu-to-cubin))' \
 // RUN: | mlir-opt -gpu-to-llvm \
 // RUN: | mlir-cpu-runner \
-// RUN:   --shared-libs=%mlir_lib_dir/libmlir_cuda_runtime%shlibext \
-// RUN:   --shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext \
+// RUN:   --shared-libs=%mlir_cuda_runtime \
+// RUN:   --shared-libs=%mlir_runner_utils \
 // RUN:   --entry-point-result=void \
 // RUN: | FileCheck %s
 
 func.func @main() {
   %data = memref.alloc() : memref<2x6xi32>
   %sum = memref.alloc() : memref<2xi32>
   %cst0 = arith.constant 0 : i32
   %cst1 = arith.constant 1 : i32

mlir/test/Integration/GPU/CUDA/all-reduce-max.mlir

 // RUN: mlir-opt %s \
 // RUN: | mlir-opt -gpu-kernel-outlining \
 // RUN: | mlir-opt -pass-pipeline='builtin.module(gpu.module(strip-debuginfo,convert-gpu-to-nvvm,gpu-to-cubin))' \
 // RUN: | mlir-opt -gpu-to-llvm \
 // RUN: | mlir-cpu-runner \
-// RUN:   --shared-libs=%mlir_lib_dir/libmlir_cuda_runtime%shlibext \
-// RUN:   --shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext \
+// RUN:   --shared-libs=%mlir_cuda_runtime \
+// RUN:   --shared-libs=%mlir_runner_utils \
 // RUN:   --entry-point-result=void \
 // RUN: | FileCheck %s
 
 func.func @main() {
   %data = memref.alloc() : memref<2x6xi32>
   %sum = memref.alloc() : memref<2xi32>
   %cst0 = arith.constant 0 : i32
   %cst1 = arith.constant 1 : i32

mlir/test/Integration/GPU/CUDA/all-reduce-min.mlir

 // RUN: mlir-opt %s \
 // RUN: | mlir-opt -gpu-kernel-outlining \
 // RUN: | mlir-opt -pass-pipeline='builtin.module(gpu.module(strip-debuginfo,convert-gpu-to-nvvm,gpu-to-cubin))' \
 // RUN: | mlir-opt -gpu-to-llvm \
 // RUN: | mlir-cpu-runner \
-// RUN:   --shared-libs=%mlir_lib_dir/libmlir_cuda_runtime%shlibext \
-// RUN:   --shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext \
+// RUN:   --shared-libs=%mlir_cuda_runtime \
+// RUN:   --shared-libs=%mlir_runner_utils \
 // RUN:   --entry-point-result=void \
 // RUN: | FileCheck %s
 
 func.func @main() {
   %data = memref.alloc() : memref<2x6xi32>
   %sum = memref.alloc() : memref<2xi32>
   %cst0 = arith.constant 0 : i32
   %cst1 = arith.constant 1 : i32

mlir/test/Integration/GPU/CUDA/all-reduce-op.mlir

 // RUN: mlir-opt %s \
 // RUN: | mlir-opt -gpu-kernel-outlining \
 // RUN: | mlir-opt -pass-pipeline='builtin.module(gpu.module(strip-debuginfo,convert-gpu-to-nvvm,gpu-to-cubin))' \
 // RUN: | mlir-opt -gpu-to-llvm \
 // RUN: | mlir-cpu-runner \
-// RUN:   --shared-libs=%mlir_lib_dir/libmlir_cuda_runtime%shlibext \
-// RUN:   --shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext \
+// RUN:   --shared-libs=%mlir_cuda_runtime \
+// RUN:   --shared-libs=%mlir_runner_utils \
 // RUN:   --entry-point-result=void \
 // RUN: | FileCheck %s
 
 // CHECK-COUNT-8: [{{(5356, ){12}5356}}]
 func.func @main() {
   %arg = memref.alloc() : memref<2x4x13xf32>
   %dst = memref.cast %arg : memref<2x4x13xf32> to memref<?x?x?xf32>
   %c0 = arith.constant 0 : index

mlir/test/Integration/GPU/CUDA/all-reduce-or.mlir

 // RUN: mlir-opt %s \
 // RUN: | mlir-opt -gpu-kernel-outlining \
 // RUN: | mlir-opt -pass-pipeline='builtin.module(gpu.module(strip-debuginfo,convert-gpu-to-nvvm,gpu-to-cubin))' \
 // RUN: | mlir-opt -gpu-to-llvm \
 // RUN: | mlir-cpu-runner \
-// RUN:   --shared-libs=%mlir_lib_dir/libmlir_cuda_runtime%shlibext \
-// RUN:   --shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext \
+// RUN:   --shared-libs=%mlir_cuda_runtime \
+// RUN:   --shared-libs=%mlir_runner_utils \
 // RUN:   --entry-point-result=void \
 // RUN: | FileCheck %s
 
 func.func @main() {
   %data = memref.alloc() : memref<2x6xi32>
   %sum = memref.alloc() : memref<2xi32>
   %cst0 = arith.constant 0 : i32
   %cst1 = arith.constant 1 : i32

mlir/test/Integration/GPU/CUDA/all-reduce-region.mlir

 // RUN: mlir-opt %s \
 // RUN: | mlir-opt -gpu-kernel-outlining \
 // RUN: | mlir-opt -pass-pipeline='builtin.module(gpu.module(strip-debuginfo,convert-gpu-to-nvvm,gpu-to-cubin))' \
 // RUN: | mlir-opt -gpu-to-llvm \
 // RUN: | mlir-cpu-runner \
-// RUN:   --shared-libs=%mlir_lib_dir/libmlir_cuda_runtime%shlibext \
-// RUN:   --shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext \
+// RUN:   --shared-libs=%mlir_cuda_runtime \
+// RUN:   --shared-libs=%mlir_runner_utils \
 // RUN:   --entry-point-result=void \
 // RUN: | FileCheck %s
 
 // CHECK: [{{(35, ){34}35}}]
 func.func @main() {
   %arg = memref.alloc() : memref<35xf32>
   %dst = memref.cast %arg : memref<35xf32> to memref<?xf32>
   %one = arith.constant 1 : index

mlir/test/Integration/GPU/CUDA/all-reduce-xor.mlir

 // RUN: mlir-opt %s \
 // RUN: | mlir-opt -gpu-kernel-outlining \
 // RUN: | mlir-opt -pass-pipeline='builtin.module(gpu.module(strip-debuginfo,convert-gpu-to-nvvm,gpu-to-cubin))' \
 // RUN: | mlir-opt -gpu-to-llvm \
 // RUN: | mlir-cpu-runner \
-// RUN:   --shared-libs=%mlir_lib_dir/libmlir_cuda_runtime%shlibext \
-// RUN:   --shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext \
+// RUN:   --shared-libs=%mlir_cuda_runtime \
+// RUN:   --shared-libs=%mlir_runner_utils \
 // RUN:   --entry-point-result=void \
 // RUN: | FileCheck %s
 
 func.func @main() {
   %data = memref.alloc() : memref<2x6xi32>
   %sum = memref.alloc() : memref<2xi32>
   %cst0 = arith.constant 0 : i32
   %cst1 = arith.constant 1 : i32

mlir/test/Integration/GPU/CUDA/async.mlir

 // RUN: mlir-opt %s \
 // RUN: | mlir-opt -gpu-kernel-outlining \
 // RUN: | mlir-opt -pass-pipeline='builtin.module(gpu.module(strip-debuginfo,convert-gpu-to-nvvm,gpu-to-cubin))' \
 // RUN: | mlir-opt -gpu-async-region -gpu-to-llvm \
 // RUN: | mlir-opt -async-to-async-runtime -async-runtime-ref-counting \
 // RUN: | mlir-opt -convert-async-to-llvm -convert-func-to-llvm \
 // RUN: | mlir-cpu-runner \
-// RUN:   --shared-libs=%mlir_lib_dir/libmlir_cuda_runtime%shlibext \
-// RUN:   --shared-libs=%mlir_lib_dir/libmlir_async_runtime%shlibext \
-// RUN:   --shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext \
+// RUN:   --shared-libs=%mlir_cuda_runtime \
+// RUN:   --shared-libs=%mlir_async_runtime \
+// RUN:   --shared-libs=%mlir_runner_utils \
 // RUN:   --entry-point-result=void -O0 \
 // RUN: | FileCheck %s
 
 func.func @main() {
   %c0    = arith.constant 0 : index
   %c1    = arith.constant 1 : index
   %count = arith.constant 2 : index
 

mlir/test/Integration/GPU/CUDA/gpu-to-cubin.mlir

 // RUN: mlir-opt %s \
 // RUN: | mlir-opt -gpu-kernel-outlining \
 // RUN: | mlir-opt -pass-pipeline='builtin.module(gpu.module(strip-debuginfo,convert-gpu-to-nvvm,gpu-to-cubin))' \
 // RUN: | mlir-opt -gpu-to-llvm \
 // RUN: | mlir-cpu-runner \
-// RUN:   --shared-libs=%mlir_lib_dir/libmlir_cuda_runtime%shlibext \
-// RUN:   --shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext \
-// RUN:   --shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext \
+// RUN:   --shared-libs=%mlir_cuda_runtime \
+// RUN:   --shared-libs=%mlir_runner_utils \
+// RUN:   --shared-libs=%mlir_c_runner_utils \
 // RUN:   --entry-point-result=void \
 // RUN: | FileCheck %s
 
 func.func @other_func(%arg0 : f32, %arg1 : memref<?xf32>) {
   %cst = arith.constant 1 : index
   %c0 = arith.constant 0 : index
   %cst2 = memref.dim %arg1, %c0 : memref<?xf32>
   gpu.launch blocks(%bx, %by, %bz) in (%grid_x = %cst, %grid_y = %cst, %grid_z = %cst)

mlir/test/Integration/GPU/CUDA/multiple-all-reduce.mlir

 // RUN: mlir-opt %s \
 // RUN: | mlir-opt -gpu-kernel-outlining \
 // RUN: | mlir-opt -pass-pipeline='builtin.module(gpu.module(strip-debuginfo,convert-gpu-to-nvvm,gpu-to-cubin))' \
 // RUN: | mlir-opt -gpu-to-llvm \
 // RUN: | mlir-cpu-runner \
-// RUN:   --shared-libs=%mlir_lib_dir/libmlir_cuda_runtime%shlibext \
-// RUN:   --shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext \
+// RUN:   --shared-libs=%mlir_cuda_runtime \
+// RUN:   --shared-libs=%mlir_runner_utils \
 // RUN:   --entry-point-result=void \
 // RUN: | FileCheck %s
 
 func.func @main() {
   %data = memref.alloc() : memref<2x6xf32>
   %sum = memref.alloc() : memref<2xf32>
   %mul = memref.alloc() : memref<2xf32>
   %cst0 = arith.constant 0.0 : f32

mlir/test/Integration/GPU/CUDA/printf.mlir

 // RUN: mlir-opt %s \
 // RUN: | mlir-opt -pass-pipeline='builtin.module(gpu.module(strip-debuginfo,convert-gpu-to-nvvm,gpu-to-cubin))' \
 // RUN: | mlir-opt -gpu-to-llvm \
 // RUN: | mlir-cpu-runner \
-// RUN:   --shared-libs=%mlir_lib_dir/libmlir_cuda_runtime%shlibext \
-// RUN:   --shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext \
+// RUN:   --shared-libs=%mlir_cuda_runtime \
+// RUN:   --shared-libs=%mlir_runner_utils \
 // RUN:   --entry-point-result=void \
 // RUN: | FileCheck %s
 
 // CHECK: Hello from 0, 2, 3.000000
 // CHECK: Hello from 1, 2, 3.000000
 module attributes {gpu.container_module} {
     gpu.module @kernels {
         gpu.func @hello() kernel {

mlir/test/Integration/GPU/CUDA/shuffle.mlir

 // RUN: mlir-opt %s \
 // RUN: | mlir-opt -gpu-kernel-outlining \
 // RUN: | mlir-opt -pass-pipeline='builtin.module(gpu.module(strip-debuginfo,convert-gpu-to-nvvm,gpu-to-cubin))' \
 // RUN: | mlir-opt -gpu-to-llvm \
 // RUN: | mlir-cpu-runner \
-// RUN:   --shared-libs=%mlir_lib_dir/libmlir_cuda_runtime%shlibext \
-// RUN:   --shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext \
+// RUN:   --shared-libs=%mlir_cuda_runtime \
+// RUN:   --shared-libs=%mlir_runner_utils \
 // RUN:   --entry-point-result=void \
 // RUN: | FileCheck %s
 
 // CHECK: [4, 5, 6, 7, 0, 1, 2, 3, 12, -1, -1, -1, 8]
 func.func @main() {
   %arg = memref.alloc() : memref<13xf32>
   %dst = memref.cast %arg : memref<13xf32> to memref<?xf32>
   %one = arith.constant 1 : index

mlir/test/Integration/GPU/CUDA/two-modules.mlir

 // RUN: mlir-opt %s \
 // RUN: | mlir-opt -gpu-kernel-outlining \
 // RUN: | mlir-opt -pass-pipeline='builtin.module(gpu.module(strip-debuginfo,convert-gpu-to-nvvm,gpu-to-cubin))' \
 // RUN: | mlir-opt -gpu-to-llvm \
 // RUN: | mlir-cpu-runner \
-// RUN:   --shared-libs=%mlir_lib_dir/libmlir_cuda_runtime%shlibext \
-// RUN:   --shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext \
+// RUN:   --shared-libs=%mlir_cuda_runtime \
+// RUN:   --shared-libs=%mlir_runner_utils \
 // RUN:   --entry-point-result=void \
 // RUN: | FileCheck %s
 
 // CHECK: [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]
 func.func @main() {
   %arg = memref.alloc() : memref<13xi32>
   %dst = memref.cast %arg : memref<13xi32> to memref<?xi32>
   %one = arith.constant 1 : index

mlir/test/Integration/GPU/ROCM/gpu-to-hsaco.mlir

 // RUN: mlir-opt %s \
 // RUN: | mlir-opt -gpu-kernel-outlining \
 // RUN: | mlir-opt -pass-pipeline='builtin.module(gpu.module(strip-debuginfo,convert-gpu-to-rocdl,gpu-to-hsaco{chip=%chip}))' \
 // RUN: | mlir-opt -gpu-to-llvm \
 // RUN: | mlir-cpu-runner \
-// RUN:   --shared-libs=%mlir_lib_dir/libmlir_rocm_runtime%shlibext \
-// RUN:   --shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext \
+// RUN:   --shared-libs=%mlir_rocm_runtime \
+// RUN:   --shared-libs=%mlir_runner_utils \
 // RUN:   --entry-point-result=void \
 // RUN: | FileCheck %s
 
 func.func @other_func(%arg0 : f32, %arg1 : memref<?xf32>) {
   %c0 = arith.constant 0 : index
   %c1 = arith.constant 1 : index
   %block_dim = memref.dim %arg1, %c0 : memref<?xf32>
   gpu.launch blocks(%bx, %by, %bz) in (%grid_x = %c1, %grid_y = %c1, %grid_z = %c1)

mlir/test/Integration/GPU/ROCM/printf.mlir

 // RUN: mlir-opt %s \
 // RUN: | mlir-opt -pass-pipeline='builtin.module(gpu.module(strip-debuginfo,convert-gpu-to-rocdl{index-bitwidth=32 runtime=HIP},gpu-to-hsaco{chip=%chip}))' \
 // RUN: | mlir-opt -gpu-to-llvm \
 // RUN: | mlir-cpu-runner \
-// RUN:   --shared-libs=%mlir_lib_dir/libmlir_rocm_runtime%shlibext \
-// RUN:   --shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext \
+// RUN:   --shared-libs=%mlir_rocm_runtime \
+// RUN:   --shared-libs=%mlir_runner_utils \
 // RUN:   --entry-point-result=void \
 // RUN: | FileCheck %s
 
 // CHECK: Hello from 0
 // CHECK: Hello from 1
 module attributes {gpu.container_module} {
     gpu.module @kernels {
         gpu.func @hello() kernel {

mlir/test/Integration/GPU/ROCM/two-modules.mlir

 // RUN: mlir-opt %s \
 // RUN: | mlir-opt -gpu-kernel-outlining \
 // RUN: | mlir-opt -pass-pipeline='builtin.module(gpu.module(strip-debuginfo,convert-gpu-to-rocdl,gpu-to-hsaco{chip=%chip}))' \
 // RUN: | mlir-opt -gpu-to-llvm \
 // RUN: | mlir-cpu-runner \
-// RUN:   --shared-libs=%mlir_lib_dir/libmlir_rocm_runtime%shlibext \
-// RUN:   --shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext \
+// RUN:   --shared-libs=%mlir_rocm_runtime \
+// RUN:   --shared-libs=%mlir_runner_utils \
 // RUN:   --entry-point-result=void \
 // RUN: | FileCheck %s
 
 // CHECK: [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]
 func.func @main() {
   %arg = memref.alloc() : memref<13xi32>
   %dst = memref.cast %arg : memref<13xi32> to memref<?xi32>
   %c0 = arith.constant 0 : index

mlir/test/Integration/GPU/ROCM/vecadd.mlir

 // RUN: mlir-opt %s \
 // RUN: | mlir-opt -convert-scf-to-cf \
 // RUN: | mlir-opt -gpu-kernel-outlining \
 // RUN: | mlir-opt -pass-pipeline='builtin.module(gpu.module(strip-debuginfo,convert-gpu-to-rocdl{use-bare-ptr-memref-call-conv=true},gpu-to-hsaco{chip=%chip}))' \
 // RUN: | mlir-opt -gpu-to-llvm=use-bare-pointers-for-kernels=true \
 // RUN: | mlir-cpu-runner \
-// RUN:   --shared-libs=%mlir_lib_dir/libmlir_rocm_runtime%shlibext \
-// RUN:   --shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext \
+// RUN:   --shared-libs=%mlir_rocm_runtime \
+// RUN:   --shared-libs=%mlir_runner_utils \
 // RUN:   --entry-point-result=void \
 // RUN: | FileCheck %s
 
 func.func @vecadd(%arg0 : memref<5xf32>, %arg1 : memref<5xf32>, %arg2 : memref<5xf32>) {
   %c0 = arith.constant 0 : index
   %c1 = arith.constant 1 : index
   %block_dim = arith.constant 5 : index
   gpu.launch blocks(%bx, %by, %bz) in (%grid_x = %c1, %grid_y = %c1, %grid_z = %c1)

mlir/test/Integration/GPU/ROCM/vector-transferops.mlir

 // RUN: mlir-opt %s \
 // RUN: | mlir-opt -convert-scf-to-cf \
 // RUN: | mlir-opt -gpu-kernel-outlining \
 // RUN: | mlir-opt -pass-pipeline='builtin.module(gpu.module(strip-debuginfo,convert-gpu-to-rocdl{chipset=%chip index-bitwidth=32},gpu-to-hsaco{chip=%chip}))' \
 // RUN: | mlir-opt -gpu-to-llvm \
 // RUN: | mlir-cpu-runner \
-// RUN:   --shared-libs=%mlir_lib_dir/libmlir_rocm_runtime%shlibext \
-// RUN:   --shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext \
+// RUN:   --shared-libs=%mlir_rocm_runtime \
+// RUN:   --shared-libs=%mlir_runner_utils \
 // RUN:   --entry-point-result=void \
 // RUN: | FileCheck %s
 
 // TODO: swap for vector transfer reads if we ever create a --vector-to-amdgpu
 func.func @vectransferx2(%arg0 : memref<?xf32>, %arg1 : memref<?xf32>) {
   %cst = arith.constant 1 : index
   gpu.launch blocks(%bx, %by, %bz) in (%grid_x = %cst, %grid_y = %cst, %grid_z = %cst)
              threads(%tx, %ty, %tz) in (%block_x = %cst, %block_y = %cst, %block_z = %cst) {

mlir/test/lit.cfg.py

 # test_exec_root: The root path where tests should be run.
 config.test_exec_root = os.path.join(config.mlir_obj_root, 'test')
 
 config.substitutions.append(('%PATH%', config.environment['PATH']))
 config.substitutions.append(('%shlibext', config.llvm_shlib_ext))
 config.substitutions.append(("%mlir_src_root", config.mlir_src_root))
 config.substitutions.append(("%host_cxx", config.host_cxx))
 config.substitutions.append(("%host_cc", config.host_cc))
+config.substitutions.append(("%mlir_vulkan_runtime_wrappers", config.mlir_vulkan_runtime_wrappers))
+config.substitutions.append(("%mlir_runner_utils", config.mlir_runner_utils))
+config.substitutions.append(("%mlir_c_runner_utils", config.mlir_c_runner_utils))
+config.substitutions.append(("%mlir_async_runtime", config.mlir_async_runtime))
+config.substitutions.append(("%mlir_cuda_runtime", config.mlir_cuda_runtime))
+config.substitutions.append(("%mlir_rocm_runtime", config.mlir_rocm_runtime))
+config.substitutions.append(("%mlir_test_spirv_cpu_runner_c_wrappers", config.mlir_test_spirv_cpu_runner_c_wrappers))
 
 llvm_config.with_system_environment(
     ['HOME', 'INCLUDE', 'LIB', 'TMP', 'TEMP'])
 
 llvm_config.use_default_substitutions()
 
 # excludes: A list of directories to exclude from the testsuite. The 'Inputs'
 # subdirectories contain auxiliary inputs for various tests in their parent
 # directories.
 config.excludes = ['Inputs', 'CMakeLists.txt', 'README.txt', 'LICENSE.txt',
                    'lit.cfg.py', 'lit.site.cfg.py']

mlir/test/lit.site.cfg.py.in

 config.llvm_use_sanitizer = "@LLVM_USE_SANITIZER@"
 config.host_arch = "@HOST_ARCH@"
 config.mlir_src_root = "@MLIR_SOURCE_DIR@"
 config.mlir_obj_root = "@MLIR_BINARY_DIR@"
 config.mlir_tools_dir = "@MLIR_TOOLS_DIR@"
 config.mlir_cmake_dir = "@MLIR_CMAKE_DIR@"
 config.mlir_lib_dir = "@MLIR_LIB_DIR@"
 
+config.mlir_vulkan_runtime_wrappers = "@MLIR_VULKAN_RUNTIME_WRAPPERS@"
+config.mlir_runner_utils = "@MLIR_RUNNER_UTILS@"
+config.mlir_c_runner_utils = "@MLIR_C_RUNNER_UTILS@"
+config.mlir_async_runtime = "@MLIR_ASYNC_RUNTIME@"
+config.mlir_cuda_runtime = "@MLIR_CUDA_RUNTIME@"
+config.mlir_rocm_runtime = "@MLIR_ROCM_RUNTIME@"
+config.mlir_test_spirv_cpu_runner_c_wrappers = "@MLIR_TEST_SPRIV_CPU_RUNNER_C_WRAPPERS@"
+
 config.build_examples = @LLVM_BUILD_EXAMPLES@
 config.run_cuda_tests = @MLIR_ENABLE_CUDA_CONVERSIONS@
 config.enable_cuda_runner = @MLIR_ENABLE_CUDA_RUNNER@
 config.run_rocm_tests = @MLIR_ENABLE_ROCM_CONVERSIONS@
 config.enable_rocm_runner = @MLIR_ENABLE_ROCM_RUNNER@
 config.rocm_test_chipset = "@ROCM_TEST_CHIPSET@"
 config.enable_spirv_cpu_runner = @MLIR_ENABLE_SPIRV_CPU_RUNNER@
 config.enable_vulkan_runner = @MLIR_ENABLE_VULKAN_RUNNER@

mlir/test/mlir-cpu-runner/X86Vector/math-polynomial-approx-avx2.mlir

 // RUN:   mlir-opt %s -test-math-polynomial-approximation="enable-avx2"        \
 // RUN:               -convert-arith-to-llvm                                   \
 // RUN:               -convert-vector-to-llvm="enable-x86vector"               \
 // RUN:               -convert-math-to-llvm                                    \
 // RUN:               -convert-func-to-llvm                                     \
 // RUN:               -reconcile-unrealized-casts                              \
 // RUN: | mlir-cpu-runner                                                      \
 // RUN:     -e main -entry-point-result=void -O0                               \
-// RUN:     -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext  \
-// RUN:     -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext    \
+// RUN:     -shared-libs=%mlir_c_runner_utils  \
+// RUN:     -shared-libs=%mlir_runner_utils    \
 // RUN: | FileCheck %s
 
 // -------------------------------------------------------------------------- //
 // rsqrt.
 // -------------------------------------------------------------------------- //
 
 func.func @rsqrt() {
   // Sanity-check that the scalar rsqrt still works OK.

mlir/test/mlir-cpu-runner/async-error.mlir

 // RUN:   mlir-opt %s -pass-pipeline="builtin.module(async-to-async-runtime,func.func(async-runtime-ref-counting,async-runtime-ref-counting-opt),convert-async-to-llvm,func.func(convert-linalg-to-loops,convert-scf-to-cf),convert-linalg-to-llvm,convert-vector-to-llvm,func.func(convert-arith-to-llvm),convert-func-to-llvm,reconcile-unrealized-casts)" \
 // RUN: | mlir-cpu-runner                                                      \
 // RUN:     -e main -entry-point-result=void -O0                               \
-// RUN:     -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext  \
-// RUN:     -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext    \
-// RUN:     -shared-libs=%mlir_lib_dir/libmlir_async_runtime%shlibext   \
+// RUN:     -shared-libs=%mlir_c_runner_utils  \
+// RUN:     -shared-libs=%mlir_runner_utils    \
+// RUN:     -shared-libs=%mlir_async_runtime   \
 // RUN: | FileCheck %s --dump-input=always
 
 // FIXME: https://github.com/llvm/llvm-project/issues/57231
 // UNSUPPORTED: hwasan
+// FIXME: Windows does not have aligned_alloc
+// UNSUPPORTED: system-windows
 
 func.func @main() {
   %false = arith.constant 0 : i1
 
   // ------------------------------------------------------------------------ //
   // Check that simple async region completes without errors.
   // ------------------------------------------------------------------------ //
   %token0 = async.execute {

mlir/test/mlir-cpu-runner/async-func.mlir

 // RUN:   mlir-opt %s -pass-pipeline="builtin.module(async-func-to-async-runtime,async-to-async-runtime,func.func(async-runtime-ref-counting,async-runtime-ref-counting-opt),convert-async-to-llvm,func.func(convert-linalg-to-loops,convert-scf-to-cf),convert-linalg-to-llvm,convert-vector-to-llvm,func.func(convert-arith-to-llvm),convert-func-to-llvm,reconcile-unrealized-casts)" \
 // RUN: | mlir-cpu-runner                                                      \
 // RUN:     -e main -entry-point-result=void -O0                               \
-// RUN:     -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext  \
-// RUN:     -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext    \
-// RUN:     -shared-libs=%mlir_lib_dir/libmlir_async_runtime%shlibext   \
+// RUN:     -shared-libs=%mlir_c_runner_utils  \
+// RUN:     -shared-libs=%mlir_runner_utils    \
+// RUN:     -shared-libs=%mlir_async_runtime   \
 // RUN: | FileCheck %s --dump-input=always
 
 // FIXME: https://github.com/llvm/llvm-project/issues/57231
 // UNSUPPORTED: hwasan
+// FIXME: Windows does not have aligned_alloc
+// UNSUPPORTED: system-windows
 
 async.func @async_func_empty() -> !async.token {
   return
 }
 
 async.func @async_func_assert() -> !async.token {
   %false = arith.constant 0 : i1
   cf.assert %false, "error"

mlir/test/mlir-cpu-runner/async-group.mlir

 // RUN:   mlir-opt %s -pass-pipeline="builtin.module(async-to-async-runtime,func.func(async-runtime-ref-counting,async-runtime-ref-counting-opt),convert-async-to-llvm,func.func(convert-arith-to-llvm),convert-func-to-llvm,reconcile-unrealized-casts)" \
 // RUN: | mlir-cpu-runner                                                      \
 // RUN:     -e main -entry-point-result=void -O0                               \
-// RUN:     -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext  \
-// RUN:     -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext    \
-// RUN:     -shared-libs=%mlir_lib_dir/libmlir_async_runtime%shlibext   \
+// RUN:     -shared-libs=%mlir_c_runner_utils  \
+// RUN:     -shared-libs=%mlir_runner_utils    \
+// RUN:     -shared-libs=%mlir_async_runtime   \
 // RUN: | FileCheck %s
 
 // This is crashing in CI "most of the time" on a AMD Rome CPU VM on GCP with:
 //    Tracer caught signal 11: addr=0x7a800028 pc=0x2e81ba sp=0x7efd2a7ffd50
 //    LeakSanitizer has encountered a fatal error.
 // This is hard to reproduce locally unfortunately. Disable it with ASAN/LSAN
 // to keep the bot green for now.
 // UNSUPPORTED: asan
 
 // FIXME: https://github.com/llvm/llvm-project/issues/57231
 // UNSUPPORTED: hwasan
+// FIXME: Windows does not have aligned_alloc
+// UNSUPPORTED: system-windows
 
 func.func @main() {
   %c1 = arith.constant 1 : index
   %c5 = arith.constant 5 : index
 
   %group = async.create_group %c5 : !async.group
 
   %token0 = async.execute { async.yield }

mlir/test/mlir-cpu-runner/async-value.mlir

 // RUN:   mlir-opt %s -pass-pipeline="builtin.module(async-to-async-runtime,func.func(async-runtime-ref-counting,async-runtime-ref-counting-opt),convert-async-to-llvm,func.func(convert-arith-to-llvm),convert-vector-to-llvm,finalize-memref-to-llvm,convert-func-to-llvm,reconcile-unrealized-casts)" \
 // RUN: | mlir-cpu-runner                                                      \
 // RUN:     -e main -entry-point-result=void -O0                               \
-// RUN:     -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext  \
-// RUN:     -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext    \
-// RUN:     -shared-libs=%mlir_lib_dir/libmlir_async_runtime%shlibext   \
+// RUN:     -shared-libs=%mlir_c_runner_utils  \
+// RUN:     -shared-libs=%mlir_runner_utils    \
+// RUN:     -shared-libs=%mlir_async_runtime   \
 // RUN: | FileCheck %s --dump-input=always
 
 // FIXME: https://github.com/llvm/llvm-project/issues/57231
 // UNSUPPORTED: hwasan
+// FIXME: Windows does not have aligned_alloc
+// UNSUPPORTED: system-windows
 
 func.func @main() {
 
   // ------------------------------------------------------------------------ //
   // Blocking async.await outside of the async.execute.
   // ------------------------------------------------------------------------ //
   %token, %result = async.execute -> !async.value<f32> {
     %0 = arith.constant 123.456 : f32

mlir/test/mlir-cpu-runner/async.mlir

 // RUN:   mlir-opt %s -pass-pipeline="builtin.module(async-to-async-runtime,func.func(async-runtime-ref-counting,async-runtime-ref-counting-opt),convert-async-to-llvm,func.func(convert-linalg-to-loops,convert-scf-to-cf),convert-linalg-to-llvm,finalize-memref-to-llvm,func.func(convert-arith-to-llvm),convert-func-to-llvm,reconcile-unrealized-casts)" \
 // RUN: | mlir-cpu-runner                                                      \
 // RUN:     -e main -entry-point-result=void -O0                               \
-// RUN:     -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext  \
-// RUN:     -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext    \
-// RUN:     -shared-libs=%mlir_lib_dir/libmlir_async_runtime%shlibext   \
+// RUN:     -shared-libs=%mlir_c_runner_utils  \
+// RUN:     -shared-libs=%mlir_runner_utils    \
+// RUN:     -shared-libs=%mlir_async_runtime   \
 // RUN: | FileCheck %s
 
 // FIXME: https://github.com/llvm/llvm-project/issues/57231
 // UNSUPPORTED: asan
 // UNSUPPORTED: hwasan
+// FIXME: Windows does not have aligned_alloc
+// UNSUPPORTED: system-windows
 
 func.func @main() {
   %i0 = arith.constant 0 : index
   %i1 = arith.constant 1 : index
   %i2 = arith.constant 2 : index
   %i3 = arith.constant 3 : index
 
   %c0 = arith.constant 0.0 : f32

mlir/test/mlir-cpu-runner/bare-ptr-call-conv.mlir

-// RUN: mlir-opt %s -pass-pipeline="builtin.module(func.func(convert-scf-to-cf,convert-arith-to-llvm),finalize-memref-to-llvm,convert-func-to-llvm{use-bare-ptr-memref-call-conv=1},reconcile-unrealized-casts)" | mlir-cpu-runner -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext -entry-point-result=void | FileCheck %s
+// RUN: mlir-opt %s -pass-pipeline="builtin.module(func.func(convert-scf-to-cf,convert-arith-to-llvm),finalize-memref-to-llvm,convert-func-to-llvm{use-bare-ptr-memref-call-conv=1},reconcile-unrealized-casts)" | mlir-cpu-runner -shared-libs=%mlir_c_runner_utils -entry-point-result=void | FileCheck %s
 
 // Verify bare pointer memref calling convention. `simple_add1_add2_test`
 // gets two 2xf32 memrefs, adds 1.0f to the first one and 2.0f to the second
 // one. 'main' calls 'simple_add1_add2_test' with {1, 1} and {2, 2} so {2, 2}
 // and {4, 4} are the expected outputs.
 
 func.func @simple_add1_add2_test(%arg0: memref<2xf32>, %arg1: memref<2xf32>) {
   %c2 = arith.constant 2 : index

mlir/test/mlir-cpu-runner/copy.mlir

 // RUN: mlir-opt %s -pass-pipeline="builtin.module(func.func(convert-scf-to-cf,convert-arith-to-llvm),finalize-memref-to-llvm,convert-func-to-llvm,reconcile-unrealized-casts)" \
 // RUN: | mlir-cpu-runner -e main -entry-point-result=void \
-// RUN: -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext,%mlir_lib_dir/libmlir_c_runner_utils%shlibext \
+// RUN: -shared-libs=%mlir_runner_utils,%mlir_c_runner_utils \
 // RUN: | FileCheck %s
 
 func.func private @printMemrefF32(memref<*xf32>) attributes { llvm.emit_c_interface }
 
 func.func @main() -> () {
   %c0 = arith.constant 0 : index
   %c1 = arith.constant 1 : index
   %c42 = arith.constant 42.0 : f32

mlir/test/mlir-cpu-runner/global-memref.mlir

-// RUN: mlir-opt %s -pass-pipeline="builtin.module(func.func(convert-arith-to-llvm),finalize-memref-to-llvm,convert-func-to-llvm,reconcile-unrealized-casts)" | mlir-cpu-runner -e main -entry-point-result=void -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext,%mlir_lib_dir/libmlir_c_runner_utils%shlibext | FileCheck %s
+// RUN: mlir-opt %s -pass-pipeline="builtin.module(func.func(convert-arith-to-llvm),finalize-memref-to-llvm,convert-func-to-llvm,reconcile-unrealized-casts)" | mlir-cpu-runner -e main -entry-point-result=void -shared-libs=%mlir_runner_utils,%mlir_c_runner_utils | FileCheck %s
 
 func.func private @printMemrefF32(memref<*xf32>) attributes { llvm.emit_c_interface }
 func.func private @printMemrefI32(memref<*xi32>) attributes { llvm.emit_c_interface }
 func.func private @printNewline() -> ()
 
 memref.global "private" @gv0 : memref<4xf32> = dense<[0.0, 1.0, 2.0, 3.0]>
 func.func @test1DMemref() {
   %0 = memref.get_global @gv0 : memref<4xf32>

mlir/test/mlir-cpu-runner/lit.local.cfg

 import sys
 
-# FIXME: llvm orc does not support the COFF rtld.
-if sys.platform == 'win32':
-    config.unsupported = True
-
 # MSAN does not work with JIT.
 if 'msan' in config.available_features:
   config.unsupported = True
 
 # Requires native execution.
 if 'host-supports-jit' not in config.available_features:
     config.unsupported = True
 
 config.available_features.add(
         config.root.native_target.lower() + '-native-target')

mlir/test/mlir-cpu-runner/math-polynomial-approx.mlir

 // RUN:   mlir-opt %s -pass-pipeline="builtin.module(func.func(test-math-polynomial-approximation,convert-arith-to-llvm),convert-vector-to-llvm,func.func(convert-math-to-llvm),convert-func-to-llvm,reconcile-unrealized-casts)" \
 // RUN: | mlir-cpu-runner                                                      \
 // RUN:     -e main -entry-point-result=void -O0                               \
-// RUN:     -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext  \
-// RUN:     -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext    \
+// RUN:     -shared-libs=%mlir_c_runner_utils  \
+// RUN:     -shared-libs=%mlir_runner_utils    \
 // RUN: | FileCheck %s
 
 // -------------------------------------------------------------------------- //
 // Tanh.
 // -------------------------------------------------------------------------- //
 
 func.func @tanh_f32(%a : f32) {
   %r = math.tanh %a : f32

mlir/test/mlir-cpu-runner/memref-reinterpret-cast.mlir

 // RUN: mlir-opt %s -pass-pipeline="builtin.module(func.func(convert-scf-to-cf),finalize-memref-to-llvm,func.func(convert-arith-to-llvm),convert-func-to-llvm,reconcile-unrealized-casts)" \
 // RUN: | mlir-cpu-runner -e main -entry-point-result=void \
-// RUN: -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext,%mlir_lib_dir/libmlir_c_runner_utils%shlibext \
+// RUN: -shared-libs=%mlir_runner_utils,%mlir_c_runner_utils \
 // RUN: | FileCheck %s
 
 func.func private @printMemrefF32(memref<*xf32>) attributes { llvm.emit_c_interface }
 
 func.func @main() -> () {
   %c0 = arith.constant 0 : index
   %c1 = arith.constant 1 : index
 

mlir/test/mlir-cpu-runner/memref-reshape.mlir

 // RUN: mlir-opt %s -pass-pipeline="builtin.module(func.func(convert-scf-to-cf,memref-expand,convert-arith-to-llvm),finalize-memref-to-llvm,convert-func-to-llvm,reconcile-unrealized-casts)" \
 // RUN: | mlir-cpu-runner -e main -entry-point-result=void \
-// RUN: -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext,%mlir_lib_dir/libmlir_c_runner_utils%shlibext \
+// RUN: -shared-libs=%mlir_runner_utils,%mlir_c_runner_utils \
 // RUN: | FileCheck %s
 
 
 func.func private @printMemrefF32(memref<*xf32>) attributes { llvm.emit_c_interface }
 
 func.func @main() -> () {
   %c0 = arith.constant 0 : index
   %c1 = arith.constant 1 : index

mlir/test/mlir-cpu-runner/print.mlir

 // RUN: mlir-opt %s -pass-pipeline="builtin.module(convert-func-to-llvm,reconcile-unrealized-casts)" \
 // RUN: | mlir-cpu-runner -e main -entry-point-result=void \
-// RUN:   -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext,%mlir_lib_dir/libmlir_c_runner_utils%shlibext \
+// RUN:   -shared-libs=%mlir_runner_utils,%mlir_c_runner_utils \
 // RUN: | FileCheck %s
 
 
 llvm.mlir.global internal constant @str_global("String to print\0A")
 llvm.func @printCString(!llvm.ptr<i8>)
 
 func.func @main() {
   %0 = llvm.mlir.addressof @str_global : !llvm.ptr<array<16 x i8>>
   %1 = llvm.mlir.constant(0 : index) : i64
   %2 = llvm.getelementptr %0[%1, %1]
     : (!llvm.ptr<array<16 x i8>>, i64, i64) -> !llvm.ptr<i8>
   llvm.call @printCString(%2) : (!llvm.ptr<i8>) -> ()
   return
 }
 
 // CHECK: String to print

mlir/test/mlir-cpu-runner/sgemm-naive-codegen.mlir

-// RUN: mlir-opt -pass-pipeline="builtin.module(func.func(convert-linalg-to-loops,lower-affine,convert-scf-to-cf,convert-arith-to-llvm),convert-vector-to-llvm,finalize-memref-to-llvm,convert-func-to-llvm,reconcile-unrealized-casts)" %s | mlir-cpu-runner -O3 -e main -entry-point-result=void -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | FileCheck %s
+// RUN: mlir-opt -pass-pipeline="builtin.module(func.func(convert-linalg-to-loops,lower-affine,convert-scf-to-cf,convert-arith-to-llvm),convert-vector-to-llvm,finalize-memref-to-llvm,convert-func-to-llvm,reconcile-unrealized-casts)" %s | mlir-cpu-runner -O3 -e main -entry-point-result=void -shared-libs=%mlir_c_runner_utils | FileCheck %s
 
 func.func @main() {
   %A = memref.alloc() : memref<16x16xf32>
   %B = memref.alloc() : memref<16x16xf32>
   %C = memref.alloc() : memref<16x16xf32>
 
   %cf1 = arith.constant 1.00000e+00 : f32
 

mlir/test/mlir-cpu-runner/simple.mlir

 // RUN: mlir-cpu-runner %s | FileCheck %s
 // RUN: mlir-cpu-runner %s -e foo | FileCheck -check-prefix=NOMAIN %s
 // RUN: mlir-cpu-runner %s --entry-point-result=i32 -e int32_main | FileCheck -check-prefix=INT32MAIN %s
 // RUN: mlir-cpu-runner %s --entry-point-result=i64 -e int64_main | FileCheck -check-prefix=INT64MAIN %s
 // RUN: mlir-cpu-runner %s -O3 | FileCheck %s
 
 // RUN: cp %s %t
 // RUN: mlir-cpu-runner %t -dump-object-file | FileCheck %t
 // RUN: ls %t.o
 // RUN: rm %t.o
 
 // RUN: mlir-cpu-runner %s -dump-object-file -object-filename=%T/test.o | FileCheck %s
 // RUN: ls %T/test.o
 // RUN: rm %T/test.o
 
 // Declarations of C library functions.
-llvm.func @fabsf(f32) -> f32
+llvm.func @logbf(f32) -> f32
 llvm.func @malloc(i64) -> !llvm.ptr<i8>
 llvm.func @free(!llvm.ptr<i8>)
 
 // Check that a simple function with a nested call works.
 llvm.func @main() -> f32 {
   %0 = llvm.mlir.constant(-4.200000e+02 : f32) : f32
-  %1 = llvm.call @fabsf(%0) : (f32) -> f32
+  %1 = llvm.call @logbf(%0) : (f32) -> f32
   llvm.return %1 : f32
 }
-// CHECK: 4.200000e+02
+// CHECK: 8.000000e+00
 
 // Helper typed functions wrapping calls to "malloc" and "free".
 llvm.func @allocation() -> !llvm.ptr<f32> {
   %0 = llvm.mlir.constant(4 : index) : i64
   %1 = llvm.call @malloc(%0) : (i64) -> !llvm.ptr<i8>
   %2 = llvm.bitcast %1 : !llvm.ptr<i8> to !llvm.ptr<f32>
   llvm.return %2 : !llvm.ptr<f32>
 }

mlir/test/mlir-cpu-runner/unranked-memref.mlir

 // RUN: mlir-opt %s -pass-pipeline="builtin.module(func.func(convert-linalg-to-loops,convert-scf-to-cf,convert-arith-to-llvm),convert-linalg-to-llvm,finalize-memref-to-llvm,convert-func-to-llvm,reconcile-unrealized-casts)" |        \
 // RUN: mlir-cpu-runner -e main -entry-point-result=void \
-// RUN: -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext,%mlir_lib_dir/libmlir_c_runner_utils%shlibext | FileCheck %s
+// RUN: -shared-libs=%mlir_runner_utils,%mlir_c_runner_utils | FileCheck %s
 
 // CHECK: rank = 2
 // CHECK-SAME: sizes = [10, 3]
 // CHECK-SAME: strides = [3, 1]
 // CHECK-COUNT-10: [10, 10, 10]
 //
 // CHECK: rank = 2
 // CHECK-SAME: sizes = [10, 3]

mlir/test/mlir-cpu-runner/utils.mlir

-// RUN: mlir-opt %s -pass-pipeline="builtin.module(func.func(convert-linalg-to-loops,convert-scf-to-cf,convert-arith-to-llvm),convert-linalg-to-llvm,finalize-memref-to-llvm,convert-func-to-llvm,reconcile-unrealized-casts)" | mlir-cpu-runner -e print_0d -entry-point-result=void -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | FileCheck %s --check-prefix=PRINT-0D
-// RUN: mlir-opt %s -pass-pipeline="builtin.module(func.func(convert-linalg-to-loops,convert-scf-to-cf,convert-arith-to-llvm),convert-linalg-to-llvm,finalize-memref-to-llvm,convert-func-to-llvm,reconcile-unrealized-casts)" | mlir-cpu-runner -e print_1d -entry-point-result=void -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | FileCheck %s --check-prefix=PRINT-1D
-// RUN: mlir-opt %s -pass-pipeline="builtin.module(func.func(convert-linalg-to-loops,convert-scf-to-cf,convert-arith-to-llvm),convert-linalg-to-llvm,finalize-memref-to-llvm,convert-func-to-llvm,reconcile-unrealized-casts)" | mlir-cpu-runner -e print_3d -entry-point-result=void -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | FileCheck %s --check-prefix=PRINT-3D
-// RUN: mlir-opt %s -pass-pipeline="builtin.module(func.func(convert-linalg-to-loops,convert-scf-to-cf,convert-arith-to-llvm),convert-linalg-to-llvm,finalize-memref-to-llvm,convert-func-to-llvm,reconcile-unrealized-casts)" | mlir-cpu-runner -e vector_splat_2d -entry-point-result=void -shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext -shared-libs=%mlir_lib_dir/libmlir_c_runner_utils%shlibext | FileCheck %s --check-prefix=PRINT-VECTOR-SPLAT-2D
+// RUN: mlir-opt %s -pass-pipeline="builtin.module(func.func(convert-linalg-to-loops,convert-scf-to-cf,convert-arith-to-llvm),convert-linalg-to-llvm,finalize-memref-to-llvm,convert-func-to-llvm,reconcile-unrealized-casts)" | mlir-cpu-runner -e print_0d -entry-point-result=void -shared-libs=%mlir_runner_utils -shared-libs=%mlir_c_runner_utils | FileCheck %s --check-prefix=PRINT-0D
+// RUN: mlir-opt %s -pass-pipeline="builtin.module(func.func(convert-linalg-to-loops,convert-scf-to-cf,convert-arith-to-llvm),convert-linalg-to-llvm,finalize-memref-to-llvm,convert-func-to-llvm,reconcile-unrealized-casts)" | mlir-cpu-runner -e print_1d -entry-point-result=void -shared-libs=%mlir_runner_utils -shared-libs=%mlir_c_runner_utils | FileCheck %s --check-prefix=PRINT-1D
+// RUN: mlir-opt %s -pass-pipeline="builtin.module(func.func(convert-linalg-to-loops,convert-scf-to-cf,convert-arith-to-llvm),convert-linalg-to-llvm,finalize-memref-to-llvm,convert-func-to-llvm,reconcile-unrealized-casts)" | mlir-cpu-runner -e print_3d -entry-point-result=void -shared-libs=%mlir_runner_utils -shared-libs=%mlir_c_runner_utils | FileCheck %s --check-prefix=PRINT-3D
+// RUN: mlir-opt %s -pass-pipeline="builtin.module(func.func(convert-linalg-to-loops,convert-scf-to-cf,convert-arith-to-llvm),convert-linalg-to-llvm,finalize-memref-to-llvm,convert-func-to-llvm,reconcile-unrealized-casts)" | mlir-cpu-runner -e vector_splat_2d -entry-point-result=void -shared-libs=%mlir_runner_utils -shared-libs=%mlir_c_runner_utils | FileCheck %s --check-prefix=PRINT-VECTOR-SPLAT-2D
 
 func.func @print_0d() {
   %f = arith.constant 2.00000e+00 : f32
   %A = memref.alloc() : memref<f32>
   memref.store %f, %A[]: memref<f32>
   %U = memref.cast %A :  memref<f32> to memref<*xf32>
   call @printMemrefF32(%U): (memref<*xf32>) -> ()
   memref.dealloc %A : memref<f32>

mlir/test/mlir-cpu-runner/x86-varargs.mlir

 // RUN: mlir-cpu-runner %s -e caller --entry-point-result=i32 | FileCheck %s
 // Varaidic argument list (va_list) and the extraction logics are ABI-specific.
 // REQUIRES: x86-native-target
+// UNSUPPORTED: system-windows
 
 // Check if variadic functions can be called and the correct variadic argument
 // can be extracted.
 
 llvm.func @caller() -> i32 {
   %0 = llvm.mlir.constant(3 : i32) : i32
   %1 = llvm.mlir.constant(2 : i32) : i32
   %2 = llvm.mlir.constant(1 : i32) : i32

mlir/test/mlir-spirv-cpu-runner/double.mlir

-// RUN: mlir-spirv-cpu-runner %s -e main --entry-point-result=void --shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext,%mlir_lib_dir/libmlir_test_spirv_cpu_runner_c_wrappers%shlibext
+// RUN: mlir-spirv-cpu-runner %s -e main --entry-point-result=void --shared-libs=%mlir_runner_utils,%mlir_test_spirv_cpu_runner_c_wrappers
 
 // CHECK: [8,  8,  8,  8,  8,  8]
 module attributes {
   gpu.container_module,
   spirv.target_env = #spirv.target_env<
     #spirv.vce<v1.0, [Shader], [SPV_KHR_variable_pointers]>,
     #spirv.resource_limits<
      max_compute_workgroup_invocations = 128,

mlir/test/mlir-spirv-cpu-runner/lit.local.cfg

 import sys
 
-# FIXME: llvm orc does not support the COFF rtld.
-if sys.platform == 'win32':
-    config.unsupported = True
-
 if not config.enable_spirv_cpu_runner:
   config.unsupported = True

mlir/test/mlir-spirv-cpu-runner/mlir_test_spirv_cpu_runner_c_wrappers.cpp

 //===- mlir_test_spirv_cpu_runner_c_wrappers.cpp - Runner testing library -===//
 //
 // Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
 // See https://llvm.org/LICENSE.txt for license information.
 // SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
 //
 //===----------------------------------------------------------------------===//
 //
 // A small library for SPIR-V cpu runner testing.
 //
 //===----------------------------------------------------------------------===//
 
 #include "mlir/ExecutionEngine/RunnerUtils.h"
 
+#ifdef _WIN32
+#define EXPORT __declspec(dllexport)
+#else
+#define EXPORT __attribute__((visibility("default")))
+#endif
+
 // NOLINTBEGIN(*-identifier-naming)
 
-extern "C" void
+extern "C" EXPORT void
 _mlir_ciface_fillI32Buffer(StridedMemRefType<int32_t, 1> *mem_ref,
                            int32_t value) {
   std::fill_n(mem_ref->basePtr, mem_ref->sizes[0], value);
 }
 
-extern "C" void
+extern "C" EXPORT void
 _mlir_ciface_fillF32Buffer1D(StridedMemRefType<float, 1> *mem_ref,
                              float value) {
   std::fill_n(mem_ref->basePtr, mem_ref->sizes[0], value);
 }
 
-extern "C" void
+extern "C" EXPORT void
 _mlir_ciface_fillF32Buffer2D(StridedMemRefType<float, 2> *mem_ref,
                              float value) {
   std::fill_n(mem_ref->basePtr, mem_ref->sizes[0] * mem_ref->sizes[1], value);
 }
 
-extern "C" void
+extern "C" EXPORT void
 _mlir_ciface_fillF32Buffer3D(StridedMemRefType<float, 3> *mem_ref,
                              float value) {
   std::fill_n(mem_ref->basePtr,
               mem_ref->sizes[0] * mem_ref->sizes[1] * mem_ref->sizes[2], value);
 }
 
 // NOLINTEND(*-identifier-naming)

mlir/test/mlir-spirv-cpu-runner/simple_add.mlir

-// RUN: mlir-spirv-cpu-runner %s -e main --entry-point-result=void --shared-libs=%mlir_lib_dir/libmlir_runner_utils%shlibext,%mlir_lib_dir/libmlir_test_spirv_cpu_runner_c_wrappers%shlibext
+// RUN: mlir-spirv-cpu-runner %s -e main --entry-point-result=void --shared-libs=%mlir_runner_utils,%mlir_test_spirv_cpu_runner_c_wrappers
 
 // CHECK: [[[7.7,    0,    0], [7.7,    0,    0], [7.7,    0,    0]], [[0,    7.7,    0], [0,    7.7,    0], [0,    7.7,    0]], [[0,    0,    7.7], [0,    0,    7.7], [0,    0,    7.7]]]
 module attributes {
   gpu.container_module,
   spirv.target_env = #spirv.target_env<
     #spirv.vce<v1.0, [Shader], [SPV_KHR_storage_buffer_storage_class, SPV_KHR_8bit_storage]>,
     #spirv.resource_limits<
      max_compute_workgroup_invocations = 128,

mlir/test/mlir-vulkan-runner/addf.mlir

-// RUN: mlir-vulkan-runner %s --shared-libs=%mlir_lib_dir/libvulkan-runtime-wrappers%shlibext,%mlir_lib_dir/libmlir_runner_utils%shlibext --entry-point-result=void | FileCheck %s
+// RUN: mlir-vulkan-runner %s --shared-libs=%mlir_vulkan_runtime_wrappers,%mlir_runner_utils --entry-point-result=void | FileCheck %s
 
 // CHECK: [3.3,  3.3,  3.3,  3.3,  3.3,  3.3,  3.3,  3.3]
 module attributes {
   gpu.container_module,
   spirv.target_env = #spirv.target_env<
     #spirv.vce<v1.0, [Shader], [SPV_KHR_storage_buffer_storage_class]>, #spirv.resource_limits<>>
 } {
   gpu.module @kernels {

mlir/test/mlir-vulkan-runner/addi.mlir

-// RUN: mlir-vulkan-runner %s --shared-libs=%mlir_lib_dir/libvulkan-runtime-wrappers%shlibext,%mlir_lib_dir/libmlir_runner_utils%shlibext --entry-point-result=void | FileCheck %s
+// RUN: mlir-vulkan-runner %s --shared-libs=%mlir_vulkan_runtime_wrappers,%mlir_runner_utils --entry-point-result=void | FileCheck %s
 
 // CHECK-COUNT-64: [3, 3, 3, 3, 3, 3, 3, 3]
 module attributes {
   gpu.container_module,
   spirv.target_env = #spirv.target_env<
     #spirv.vce<v1.0, [Shader], [SPV_KHR_storage_buffer_storage_class]>, #spirv.resource_limits<>>
 } {
   gpu.module @kernels {

mlir/test/mlir-vulkan-runner/addi8.mlir

-// RUN: mlir-vulkan-runner %s --shared-libs=%mlir_lib_dir/libvulkan-runtime-wrappers%shlibext,%mlir_lib_dir/libmlir_runner_utils%shlibext --entry-point-result=void | FileCheck %s
+// RUN: mlir-vulkan-runner %s --shared-libs=%mlir_vulkan_runtime_wrappers,%mlir_runner_utils --entry-point-result=void | FileCheck %s
 
 // CHECK-COUNT-64: [3, 3, 3, 3, 3, 3, 3, 3]
 module attributes {
   gpu.container_module,
   spirv.target_env = #spirv.target_env<
     #spirv.vce<v1.0, [Shader], [SPV_KHR_storage_buffer_storage_class, SPV_KHR_8bit_storage]>, #spirv.resource_limits<>>
 } {
   gpu.module @kernels {

mlir/test/mlir-vulkan-runner/mulf.mlir

-// RUN: mlir-vulkan-runner %s --shared-libs=%mlir_lib_dir/libvulkan-runtime-wrappers%shlibext,%mlir_lib_dir/libmlir_runner_utils%shlibext --entry-point-result=void | FileCheck %s
+// RUN: mlir-vulkan-runner %s --shared-libs=%mlir_vulkan_runtime_wrappers,%mlir_runner_utils --entry-point-result=void | FileCheck %s
 
 // CHECK-COUNT-4: [6, 6, 6, 6]
 module attributes {
   gpu.container_module,
   spirv.target_env = #spirv.target_env<
     #spirv.vce<v1.0, [Shader], [SPV_KHR_storage_buffer_storage_class]>, #spirv.resource_limits<>>
 } {
   gpu.module @kernels {

mlir/test/mlir-vulkan-runner/smul_extended.mlir

 // Make sure that signed extended multiplication produces expected results
 // with and without expansion to primitive mul/add ops for WebGPU.
 
 // RUN: mlir-vulkan-runner %s \
-// RUN:  --shared-libs=%mlir_lib_dir/libvulkan-runtime-wrappers%shlibext,%mlir_lib_dir/libmlir_runner_utils%shlibext \
+// RUN:  --shared-libs=%mlir_vulkan_runtime_wrappers,%mlir_runner_utils \
 // RUN:  --entry-point-result=void | FileCheck %s
 
 // RUN: mlir-vulkan-runner %s --vulkan-runner-spirv-webgpu-prepare \
-// RUN:  --shared-libs=%mlir_lib_dir/libvulkan-runtime-wrappers%shlibext,%mlir_lib_dir/libmlir_runner_utils%shlibext \
+// RUN:  --shared-libs=%mlir_vulkan_runtime_wrappers,%mlir_runner_utils \
 // RUN:  --entry-point-result=void | FileCheck %s
 
 // CHECK: [0, 1, -2,  1, 1048560, -87620295, -131071,  560969770]
 // CHECK: [0, 0, -1,  0,       0,        -1,       0, -499807318]
 module attributes {
   gpu.container_module,
   spirv.target_env = #spirv.target_env<
     #spirv.vce<v1.4, [Shader], [SPV_KHR_storage_buffer_storage_class]>, #spirv.resource_limits<>>

mlir/test/mlir-vulkan-runner/subf.mlir

-// RUN: mlir-vulkan-runner %s --shared-libs=%mlir_lib_dir/libvulkan-runtime-wrappers%shlibext,%mlir_lib_dir/libmlir_runner_utils%shlibext --entry-point-result=void | FileCheck %s
+// RUN: mlir-vulkan-runner %s --shared-libs=%mlir_vulkan_runtime_wrappers,%mlir_runner_utils --entry-point-result=void | FileCheck %s
 
 // CHECK-COUNT-32: [2.2, 2.2, 2.2, 2.2]
 module attributes {
   gpu.container_module,
   spirv.target_env = #spirv.target_env<
     #spirv.vce<v1.0, [Shader], [SPV_KHR_storage_buffer_storage_class]>,
     #spirv.resource_limits<>>
 } {

mlir/test/mlir-vulkan-runner/time.mlir

-// RUN: mlir-vulkan-runner %s --shared-libs=%mlir_lib_dir/libvulkan-runtime-wrappers%shlibext,%mlir_lib_dir/libmlir_runner_utils%shlibext --entry-point-result=void | FileCheck %s
+// RUN: mlir-vulkan-runner %s --shared-libs=%mlir_vulkan_runtime_wrappers,%mlir_runner_utils --entry-point-result=void | FileCheck %s
 
 // CHECK: Compute shader execution time
 // CHECK: Command buffer submit time
 // CHECK: Wait idle time
 
 module attributes {
   gpu.container_module,
   spirv.target_env = #spirv.target_env<

mlir/test/mlir-vulkan-runner/umul_extended.mlir

 // Make sure that unsigned extended multiplication produces expected results
 // with and without expansion to primitive mul/add ops for WebGPU.
 
 // RUN: mlir-vulkan-runner %s \
-// RUN:  --shared-libs=%mlir_lib_dir/libvulkan-runtime-wrappers%shlibext,%mlir_lib_dir/libmlir_runner_utils%shlibext \
+// RUN:  --shared-libs=%mlir_vulkan_runtime_wrappers,%mlir_runner_utils \
 // RUN:  --entry-point-result=void | FileCheck %s
 
 // RUN: mlir-vulkan-runner %s --vulkan-runner-spirv-webgpu-prepare \
-// RUN:  --shared-libs=%mlir_lib_dir/libvulkan-runtime-wrappers%shlibext,%mlir_lib_dir/libmlir_runner_utils%shlibext \
+// RUN:  --shared-libs=%mlir_vulkan_runtime_wrappers,%mlir_runner_utils \
 // RUN:  --entry-point-result=void | FileCheck %s
 
 // CHECK: [0, 1, -2,  1, 1048560, -87620295, -131071, -49]
 // CHECK: [0, 0,  1, -2,       0,     65534, -131070,   6]
 module attributes {
   gpu.container_module,
   spirv.target_env = #spirv.target_env<
     #spirv.vce<v1.4, [Shader], [SPV_KHR_storage_buffer_storage_class]>, #spirv.resource_limits<>>