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[TRTLLMINF-474][infra] Upgrade NGC PyTorch base image to 26.09 - #19679
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Included review availability: This review used your included allowance. Your plan provides up to 12 included reviews per hour; 11 remain after this review. WalkthroughDocker targets and package references use updated CUDA and PyTorch versions. Jenkins image tags use a new build identifier. The Mooncake installation script removes a generated package directory, and four locality-domain tests now require the feature to be enabled. ChangesRuntime version updates
Mooncake package cleanup
Locality-domain test gating
Priority: ➖ Normal Estimated code review effort: 2 (Simple) | ~12 minutes Change: Other Suggested reviewers: Merge Risk: 🔵 Low · up to The changed release-notes links are currently unavailable, so developers cannot reach the referenced documentation. This is a bounded documentation issue; no other actionable merge risk was established. 🚥 Pre-merge checks | ✅ 4 | ❌ 1❌ Failed checks (1 warning)
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Full details: Description checkExplanation The description includes a useful change summary and a completed checklist. However, the required Description and Test Coverage sections contain only template comments, so the issue, solution, and validation details are incomplete.
✨ Finishing Touches 💡 1🛠️ Fix failing CI checks 💡
🧪 Generate unit tests (beta)
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Inline comments:
Review comments at @docker/common/install_pytorch.sh:
- Line 15: Update both PyTorch release-notes URL references from version 26.09
to the published 26.08 page, including the reference beside the install script’s
release-notes comment and the matching dependency reference.
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docker/Dockerfile.multidocker/Makefiledocker/common/install_cuda_libs.shdocker/common/install_pytorch.shjenkins/L0_Test.groovyrequirements.txt
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- 🪄 Fix CodeRabbit comments on this PR
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Review comments at @jenkins/current_image_tags.properties:
- Around line 16-17: Update LLM_DOCKER_IMAGE and LLM_SBSA_DOCKER_IMAGE to use
the 26.09-py3 PyTorch artifacts, preserving their architecture-specific suffixes
and remaining URI components.
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/bot run --stage-list "Build-Docker-Images" |
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PR_Github #76636 [ run ] triggered by Bot. Commit: |
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Signed-off-by: Emma Qiao <qqiao@nvidia.com>
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Co-authored-by: Eric Work <work.eric@gmail.com> Signed-off-by: Emma Qiao <qqiao@nvidia.com>
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PR_Github #76900 [ run ] triggered by Bot. Commit: |
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PR_Github #76900 [ run ] completed with state |
… (#20146) Signed-off-by: EmmaQiaoCh <qqiao@nvidia.com> Signed-off-by: Emma Qiao <qqiao@nvidia.com> Co-authored-by: Eric Work <work.eric@gmail.com>
…er on the 26.09 image The NGC PyTorch 26.09 base ships CUDA forward-compatibility driver 615.71.09 (26.08 shipped 615.65.02). Under it the unchanged trtllm-gen context FMHA cubin runs 7-13% slower per call on GB200, which costs aggr-ctx_only-gb200_deepseek-r1-fp4_128k8k_con1_ctx1_pp8_gen1_tep8_eplb0_mtp3_ccb-NIXL ~6% Total Token Throughput since NVIDIA#19679. Add a CUDA_COMPAT_TAG build arg (default 26.08-py3) and replace the base image's /usr/local/cuda-13.4/compat driver libraries with that tag's during the devel stage. The CUDA toolkit is untouched, and the base image's shell init still validates and selects the compat driver at container start. Targets built on nvcr.io/nvidia/cuda keep their own compat driver. Signed-off-by: chenfeiz0326 <203214996+chenfeiz0326@users.noreply.github.com>
…er on the 26.09 image The NGC PyTorch 26.09 base ships CUDA forward-compatibility driver 615.71.09 (26.08 shipped 615.65.02). Under it the unchanged trtllm-gen context FMHA cubin runs 7-13% slower per call on GB200, which costs aggr-ctx_only-gb200_deepseek-r1-fp4_128k8k_con1_ctx1_pp8_gen1_tep8_eplb0_mtp3_ccb-NIXL ~6% Total Token Throughput since NVIDIA#19679. Add a CUDA_COMPAT_TAG build arg (default 26.08-py3) and replace the base image's /usr/local/cuda-13.4/compat driver libraries with that tag's during the devel stage. The CUDA toolkit is untouched, and the base image's shell init still validates and selects the compat driver at container start. Targets built on nvcr.io/nvidia/cuda keep their own compat driver. Signed-off-by: chenfeiz0326 <203214996+chenfeiz0326@users.noreply.github.com>
Dev Engineer Review
The PyTorch base image and Jenkins L0 test image now use
26.09-py3. The Triton base image remains at26.08-py3. CUDA base tags move to13.4.1, and the cuDNN, NCCL, and cuBLAS pins move to9.26.0.51-1,2.31.2-1+cuda13.4, and13.8.0.4-1. Thenvidia-nccl-cu13requirement now allows versions from2.30.7through2.31.2.The Mooncake install script removes the CMake-generated
mooncakepackage before wheel installation. Verify that the derivedsys.pathlocation is the intended package and that cleanup preserves the wheel-based client.The test fixture change limits nested mempool tests to systems where locality-domain functionality is enabled, not only supported. CI reports failed pipelines for several commits, including runs where helper jobs succeeded. Failure details are not supplied. Advisory reviews reported PASS for inspected paths, but did not run builds or tests or verify external image and package availability.
QA Engineer Review
tests/unittest/_torch/thop/parallel/test_locality_domain_utils.pywas modified. A module-scopedcheck_locality_domain_enabledfixture skips tests unless locality-domain functionality is enabled. Four nested-mempool tests now use this fixture; they cover nested domain scopes and mempool behavior. This unit test file does not apply to the integrationtest-db/or manualqa/lists. No test execution result is available. Coverage verdict: needs follow-up.Per-File QA Perspective
docker/Dockerfile.multi: Verify that the default PyTorch image resolves to26.09-py3and the Triton image remains at26.08-py3.docker/Makefile: Verify that the four Rocky Linux 8 and Ubuntu 22/24 build targets use CUDA base image tag13.4.1.docker/common/install_cuda_libs.sh: Verify installation of cuDNN9.26.0.51-1, NCCL2.31.2-1+cuda13.4, and cuBLAS13.8.0.4-1.docker/common/install_mooncake.sh: Verify that cleanup targets only the CMake-generated package and that the wheel-based client imports and operates correctly.docker/common/install_pytorch.sh: The release-notes comment now points to release 26-09. No runtime behavior change is indicated.jenkins/L0_Test.groovy: Verify that the L0 test job selects the26.09-py3PyTorch image.jenkins/current_image_tags.properties: Verify that CI resolves the refreshed image references to the intended staged images.requirements.txt: Verify dependency resolution with NCCL versions in the>=2.30.7,<=2.31.2range. The Triton pin remains unchanged.tests/unittest/_torch/thop/parallel/test_locality_domain_utils.py: The new enabled-state fixture skips locality-domain tests when the feature is unavailable. Verify the four nested-mempool tests on enabled hardware and confirm expected skips when the feature is only supported, but disabled.Description
Test Coverage
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PR Follows TRT-LLM CODING GUIDELINES to the best of your knowledge.
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