Use static linkage for CUDA runtime #680
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📝 WalkthroughWalkthroughRemoved the Changes
Estimated code review effort🎯 2 (Simple) | ⏱️ ~10 minutes Pre-merge checks✅ Passed checks (3 passed)
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robertmaynard
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I believe we are missing changes to conda/recipes/*, and dependencies.yaml ( usage of nvidia-cudart )
bdice
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🔔 Hi @anandhkb, this pull request has had no activity for 7 days. Please update or let us know if it can be closed. Thank you! If this is an "epic" issue, then please add the "epic" label to this issue. |
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How much increase in library size should we expect ? |
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📜 Review details
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Review profile: CHILL
Plan: Pro
📒 Files selected for processing (5)
conda/recipes/cuopt/recipe.yamlconda/recipes/libcuopt/recipe.yamlcpp/CMakeLists.txtpython/cuopt/cuopt/linear_programming/CMakeLists.txtpython/libcuopt/CMakeLists.txt
🚧 Files skipped from review as they are similar to previous changes (2)
- conda/recipes/cuopt/recipe.yaml
- python/cuopt/cuopt/linear_programming/CMakeLists.txt
🧰 Additional context used
🧠 Learnings (10)
📓 Common learnings
Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cuh,cpp,hpp,h} : Check that hard-coded GPU device IDs and resource limits are made configurable; abstract multi-backend support for different CUDA versions
📚 Learning: 2025-11-25T10:20:49.822Z
Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cuh,cpp,hpp,h} : Check that hard-coded GPU device IDs and resource limits are made configurable; abstract multi-backend support for different CUDA versions
Applied to files:
cpp/CMakeLists.txtpython/libcuopt/CMakeLists.txt
📚 Learning: 2025-11-25T10:20:49.822Z
Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*benchmark*.{cpp,cu,py} : Include performance benchmarks and regression detection for GPU operations; verify near real-time performance on million-variable problems
Applied to files:
cpp/CMakeLists.txtpython/libcuopt/CMakeLists.txt
📚 Learning: 2025-11-25T10:20:49.822Z
Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cuh,cpp,hpp,h} : Track GPU device memory allocations and deallocations to prevent memory leaks; ensure cudaMalloc/cudaFree balance and cleanup of streams/events
Applied to files:
cpp/CMakeLists.txtpython/libcuopt/CMakeLists.txt
📚 Learning: 2025-11-25T10:20:49.822Z
Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cuh,cpp,hpp,h} : Refactor code duplication in solver components (3+ occurrences) into shared utilities; for GPU kernels, use templated device functions to avoid duplication
Applied to files:
cpp/CMakeLists.txtpython/libcuopt/CMakeLists.txt
📚 Learning: 2025-11-25T10:20:49.822Z
Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*test*.{cpp,cu,py} : Ensure test isolation: prevent GPU state, cached memory, and global variables from leaking between test cases; verify each test independently initializes its environment
Applied to files:
cpp/CMakeLists.txtpython/libcuopt/CMakeLists.txt
📚 Learning: 2025-11-25T10:20:49.822Z
Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cuh,cpp,hpp,h} : Ensure race conditions are absent in multi-GPU code and multi-threaded server implementations; verify proper synchronization of shared state
Applied to files:
cpp/CMakeLists.txtpython/libcuopt/CMakeLists.txt
📚 Learning: 2025-11-25T10:20:49.822Z
Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cuh,cpp,hpp,h} : Verify error propagation from CUDA to user-facing APIs is complete; ensure CUDA errors are caught and mapped to meaningful user error codes
Applied to files:
cpp/CMakeLists.txtpython/libcuopt/CMakeLists.txt
📚 Learning: 2025-11-25T10:20:49.822Z
Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cuh} : Avoid reinventing functionality already available in Thrust, CCCL, or RMM libraries; prefer standard library utilities over custom implementations
Applied to files:
python/libcuopt/CMakeLists.txt
📚 Learning: 2025-11-25T10:20:49.822Z
Learnt from: CR
Repo: NVIDIA/cuopt PR: 0
File: .github/.coderabbit_review_guide.md:0-0
Timestamp: 2025-11-25T10:20:49.822Z
Learning: Applies to **/*.{cu,cpp,hpp,h} : Avoid inappropriate use of exceptions in performance-critical GPU operation paths; prefer error codes or CUDA error checking for latency-sensitive code
Applied to files:
python/libcuopt/CMakeLists.txt
⏰ Context from checks skipped due to timeout of 90000ms. You can increase the timeout in your CodeRabbit configuration to a maximum of 15 minutes (900000ms). (9)
- GitHub Check: wheel-build-cuopt-mps-parser / 13.0.2, 3.12, amd64, rockylinux8
- GitHub Check: wheel-build-cuopt-mps-parser / 13.0.2, 3.13, arm64, rockylinux8
- GitHub Check: wheel-build-cuopt-mps-parser / 13.0.2, 3.11, amd64, rockylinux8
- GitHub Check: wheel-build-cuopt-mps-parser / 13.0.2, 3.10, amd64, rockylinux8
- GitHub Check: wheel-build-cuopt-mps-parser / 13.0.2, 3.11, arm64, rockylinux8
- GitHub Check: wheel-build-cuopt-mps-parser / 13.0.2, 3.10, arm64, rockylinux8
- GitHub Check: wheel-build-cuopt-mps-parser / 13.0.2, 3.13, amd64, rockylinux8
- GitHub Check: wheel-build-cuopt-mps-parser / 13.0.2, 3.12, arm64, rockylinux8
- GitHub Check: wheel-build-cuopt-sh-client / 13.0.2, 3.10, amd64, rockylinux8
🔇 Additional comments (5)
python/libcuopt/CMakeLists.txt (2)
2-2: LGTM: Copyright year updated appropriately.The copyright year update reflects the current development period.
1-95: LGTM: Removal of local CUDA_STATIC_RUNTIME setting is correct.The removal of
set(CUDA_STATIC_RUNTIME ON)aligns with the PR objective to centralize static CUDA runtime configuration incpp/CMakeLists.txt. The Python wrapper now inherits the static linking behavior from the parent build configuration.cpp/CMakeLists.txt (1)
2-2: LGTM: Copyright year updated appropriately.The copyright year range update reflects the current development period.
conda/recipes/libcuopt/recipe.yaml (2)
1-1: LGTM: Copyright year updated appropriately.The copyright year update reflects the current development period.
65-79: LGTM: Conda recipe changes align with static CUDA runtime linking.The removal of
cuda-cudart-devfrom host requirements andcuda-cudartfromignore_run_exportsis correct for static CUDA runtime linking. Withcudart_staticembedded in the binaries, there's no runtime dependency on the dynamic CUDA runtime library.The static CUDA runtime library should be provided by the CUDA compiler package (
${{ compiler("cuda") }}) or implicitly throughcuda-version, which appears to be correctly specified in the build and host requirements.Also applies to: 95-117, 140-169, 190-213
Minimal. Something like 1-2 MB. |
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/merge |
4 participants
This PR removes the
CUDA_STATIC_RUNTIMEoption and always uses static linking for the CUDA runtime (cudart_static).Changes
CUDA_STATIC_RUNTIMEoption fromcpp/CMakeLists.txtrapids_cuda_init_runtime(USE_STATIC ${CUDA_STATIC_RUNTIME})torapids_cuda_init_runtime(USE_STATIC ON)set(CUDA_STATIC_RUNTIME ON)from Python CMakeLists.txt filesMotivation
Static linking embeds the CUDA runtime into binaries, eliminating runtime dependency on
cuda-cudartconda packages and simplifying deployment.Related
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