[Build] Add OpenAI triton_kernels

[varun-sundar-rabindranath]

Purpose

This PR adds https://github.com/triton-lang/triton/tree/main/python/triton_kernels to vLLM.
We can't install this package via pip. Please take a look at #27659 . As a result, this PR, injects the triton_kernels package directly into vLLM during build time, similar to the approach we take with vllm_flash_attn. Concretely, we just copy the entire triton_kernels folder in <triton-root>/python/triton_kernels/triton_kernels to vllm/third_party/triton_kernelsduring build time and add the module to the sys.module["triton_kernel"] during run-time.

Fixes : #27672

Test Plan

local-build testing on H100 : python3 setup.py build_ext --inplace / uv pip install -vvv -e . --no-build-isolation
package-build testing on H100 : TORCH_CUDA_ARCH_LIST="9.0" python3 setup.py bdist_wheel --dist-dir=dist

gpt-oss serve command: vllm serve openai/gpt-oss-20b --tensor-parallel-size 2 --no-enable-prefix-caching --port 9010
gpt-oss eval command : OPENAI_API_KEY=empty python -m gpt_oss.evals --model openai/gpt-oss-20b --eval gpqa --n-threads 128 --reasoning-effort low --base-url http://localhost:9010/v1

Test Result

local-build : The build correctly copies triton_kernels into vllm/third_party/triton_kernels
package-build : The wheel when installed has triton_kernels in <site-packages>/vllm/third_party/triton_kernels
Both local_build and package-build obtains expected eval score of about 0.57.

Need to perform further testing with CI wheels.

Thanks @zyongye @daniel-fahey for the insights.

[gemini-code-assist]

Code Review

This pull request adds the build infrastructure to fetch and install OpenAI Triton kernels as a third-party dependency for CUDA builds. The changes are similar to how other external projects are handled.

My review identified two critical issues that need to be addressed:

1. In cmake/external_projects/triton_kernels.cmake, an incorrect path with a trailing slash will cause the kernel files to be installed in the wrong directory, potentially overwriting other files.
2. In setup.py, an unconditional shutil.copytree call will cause non-CUDA builds to fail because the source directory for Triton kernels will not exist.

Additionally, there appears to be a discrepancy in how the Triton kernels are being installed versus how they are imported in the codebase. The current setup installs them as vllm.third_party.triton_kernels, but existing code seems to expect a top-level triton_kernels package. This should be clarified and aligned to prevent import errors at runtime.

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[varun-sundar-rabindranath]

@codex review

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[varun-sundar-rabindranath]

@codex review

[varun-sundar-rabindranath]

cc @zyongye @robertgshaw2-redhat @simon-mo PTAL! Thanks 🙌

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[varun-sundar-rabindranath]

This is the only place where we decide what triton_kernels module to use. Perhaps we can add a VLLM_FORCE_USE_LOCAL_TRITON_KERNELS to pick the triton_kernels from vllm.third_party.triton_kernels - but I don't see the need for it now.

[varun-sundar-rabindranath]

@codex review

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[chatgpt-codex-connector]

FetchContent triton_kernels lacks CMakeLists guard

The new FetchContent declaration points CMake at python/triton_kernels/triton_kernels without overriding CONFIGURE_COMMAND/BUILD_COMMAND, so FetchContent_MakeAvailable will try to run add_subdirectory on that directory. The upstream triton_kernels package is pure Python and has no CMakeLists.txt in that path, so any CUDA/HIP build will fail during CMake configure before the Python files are installed, preventing triton_kernels from being packaged at all.

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[varun-sundar-rabindranath]

Lets wait for the CI. I had the configure and build commands set to an empty string, but cmake complained (warnings) and I removed it. I could build it locally also.

[varun-sundar-rabindranath]

Based on a prior test run - https://buildkite.com/vllm/ci/builds/39432#019a94c7-7b73-420b-8d94-25da33d57f4f , I could see tests/kernels/moe/test_gpt_oss_triton_kernels.py run successfully for CUDA build. (Note that that test will run iff triton_kernels package is present)

Still need to verify if RocM build works for the same test. I see the AMD package being built successfully (https://buildkite.com/vllm/ci/builds/39432#019a94c7-7c06-477c-a056-0715a47c47e5) - but unfortunately, it looks like there aren't any AMD tests running on PRs ? @mgoin anything we can do here ?

[mgoin]

LGTM reading through. Let's make sure we see CI tests dependent on the install running

[varun-sundar-rabindranath]

LGTM reading through. Let's make sure we see CI tests dependent on the install running

I believe test_gpt_oss_triton_kernels.py is the only dependent test.

:~/code/vllm/tests (varun/vendor-triton-kernels) $ grep -rin has_triton_kernels ./ 
./kernels/moe/test_gpt_oss_triton_kernels.py:9:from vllm.utils.import_utils import has_triton_kernels
./kernels/moe/test_gpt_oss_triton_kernels.py:11:if not has_triton_kernels():

[varun-sundar-rabindranath]

Failing tests :

• buildkite/ci/pr/entrypoints-integration-test-api-server similar error on main in commit bf9e1e8

• buildkite/ci/pr/examples-test Fails on Nightly.

• I verified that the installation dependent test for the CUDA has run successfully.

• From the logs, I see that the AMD build has the triton_kernels packaged. (note there are not AMD tests run on the PR)

I believe this is good to land - and we can verify the nightly wheels tomorrow. Thanks.

cc @mgoin @simon-mo @robertgshaw2-redhat

[varun-sundar-rabindranath]

Tested nightly on H100, with

uv pip install vllm --extra-index-url https://wheels.vllm.ai/nightly
vllm serve openai/gpt-oss-20b --tensor-parallel-size 2  --no-enable-prefix-caching  --port 9010

I could see vllm using the packaged the triton_kernels and the gpt-oss eval works fine.

I installed triton_kernels using triton_kernels @ git+https://github.com/triton-lang/[email protected]#subdirectory=python/triton_kernels after initial test and re-ran the vllm serve * command.

I could see vllm using the system triton_kernels and the gpt-oss eval works fine.