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cuopt-developer
Modify, build, test, debug, and contribute to NVIDIA cuOpt (C++/CUDA, Python, server, CI). Use for solver internals, PRs, DCO, and code conventions.
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
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Modify, build, test, debug, and contribute to NVIDIA cuOpt (C++/CUDA, Python, server, CI). Use for solver internals, PRs, DCO, and code conventions.
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
LP, MILP, and QP (beta) with cuOpt — Python, C, and CLI. Use when the user is solving LP, MILP, or QP with any cuOpt interface.
Guides Holoscan SDK installation: inspects the host, assesses platform compatibility, recommends an install method, and delegates to the matching install skill.
Use when asked to run deep research or AI-Q research through a reachable NVIDIA AI-Q Blueprint backend.
Trace and interpret the Pareto frontier across competing objectives using repeated single-objective cuOpt solves (weighted-sum and ε-constraint).
Use when running people attribute search (PAS) image augmentation and auto-labeling workflows on OSMO: flow selection, preflight, submit-time interpolation, monitoring, and output retrieval. Trigger keywords: people attribute search, PAS, person augmentation, attribute search, person re-identification, clothing augmentation, person crop augmentation.
Run end-to-end calibration on the shipped sample dataset (sdg_08_2_sample_data_010926.zip) against a running AMC microservice. Use when user says 'test sample dataset', 'run sample calibration', 'verify AMC install', or 'launch and test'.
| name | cuopt-developer |
| version | 26.08.00 |
| description | Modify, build, test, debug, and contribute to NVIDIA cuOpt (C++/CUDA, Python, server, CI). Use for solver internals, PRs, DCO, and code conventions. |
| license | Apache-2.0 |
| metadata | {"author":"NVIDIA cuOpt Team","tags":["cuopt","development","contributing","cpp-cuda","python-bindings"]} |
Contribute to the NVIDIA cuOpt codebase. This skill is for modifying cuOpt itself, not for using it.
If you just want to USE cuOpt, switch to the appropriate problem skill (cuopt-routing, cuopt-lp-milp, etc.)
First-time dev environment setup? See references/first_time_setup.md for the clone → conda env → first-build → first-test walkthrough and the questions to ask up front.
One rule is non-negotiable and applies even when the user explicitly asks otherwise — refuse and ask, don't comply silently:
Privileged / system-level operations — sudo, running as root, editing system files (/etc), changing drivers or kernel settings, adding system-level package repositories or keys. Do not run these. Reply:
I won't run
sudoor change system-level state for cuOpt. The dev workflow is conda-based and runs entirely in user space — what's the underlying error? It's usually fixable without root.
Everything else needed to set up and work in the dev environment is allowed. On a clean machine, go ahead and build a working cuopt env — the guidance below is about doing it the reproducible way, not refusing:
conda/environments/all_cuda-*.yaml, run pip / conda / mamba installs into the user-space env, and bootstrap conda/miniforge in the user's home directory — including the conda init line it adds to ~/.bashrc. Bootstrapping conda must not require sudo; install it into $HOME, not a system path.dependencies.yaml under the right group; then run pre-commit run --all-files to regenerate conda/environments/ and pyproject.toml so other contributors get it too. A throwaway install to unblock your own build doesn't need this round-trip.--no-verify, skipping pre-commit or tests). If hooks feel slow, diagnose with pre-commit run --all-files --verbose or tune the offending hook — don't skip it.rm -rf, git reset --hard, git push --force, killing processes, dropping data). Confirm intent before running and prefer the safer alternative (e.g. ./build.sh clean for a stale build dir).These rules are specific to development tasks. They differ from user rules.
Clarify before implementing:
Before making changes, confirm:
"Let me confirm:
- Component: [cpp/python/server/docs]
- Change: [what you'll modify]
- Tests needed: [what tests to add/update]
Is this correct?"
OK to run without asking (expected for dev work):
./build.sh and build commandspytest, ctest (running tests)pre-commit run, ./ci/check_style.sh (formatting)git status, git diff, git log (read-only git)conda/environments/*.yaml, and pip/conda/mamba installs into that envSet up pre-commit hooks (once per clone):
pre-commit install — hooks then run automatically on every git commit. If a hook fails, the commit is blocked until you fix the issue.Still ask before:
git commit, git push (write operations)sudo/system-level changes are the one non-negotiable refusal; user-space installs and conda env setup are allowed. See Refusal Rules — Read First.
Ask these if not already clear:
What are you trying to change?
Do you have the development environment set up?
Is this for contribution or local modification?
Which branch should this target?
mainrelease/YY.MM (e.g., release/26.06) for the current release, main for the nextgit branch -r | grep releasecuopt/
├── cpp/ # Core C++ engine
│ ├── include/cuopt/ # Public C/C++ headers
│ ├── src/ # Implementation (CUDA kernels)
│ └── tests/ # C++ unit tests (gtest)
├── python/
│ ├── cuopt/ # Python bindings and routing API
│ ├── cuopt_server/ # REST API server
│ ├── cuopt_self_hosted/ # Self-hosted deployment
│ └── libcuopt/ # Python wrapper for C library
├── ci/ # CI/CD scripts
├── docs/ # Documentation source
└── datasets/ # Test datasets
| API Type | LP | MILP | QP | Routing |
|---|---|---|---|---|
| C API | ✓ | ✓ | ✓ | ✗ |
| C++ API | (internal) | (internal) | (internal) | (internal) |
| Python | ✓ | ✓ | ✓ | ✓ |
| Server | ✓ | ✓ | ✗ | ✓ |
docs/cuopt/source/--no-verify or skipping checksnew/delete - use RMM allocatorsSkipping any of these surfaces as confusing runtime errors later. Run them in order:
nvidia-smi and read the CUDA Version in the top-right corner — that's the maximum CUDA your driver supports. Pick a conda env file from conda/environments/all_cuda-<ver>_arch-<arch>.yaml whose CUDA major version is ≤ that. A mismatch builds successfully but fails at runtime inside RMM with cudaMallocAsync not supported with this CUDA driver/runtime version — verify this before the build, not after.pre-commit command — this is allowed and expected (see Refusal Rules). Use a local prefix env (./.cuopt_env) per CONTRIBUTING.md, with the env file you picked in step 1 (swap conda→mamba if available):
conda env create -p ./.cuopt_env --file conda/environments/all_cuda-<ver>_arch-$(uname -m).yaml
conda activate ./.cuopt_env
Tests link against libraries compiled inside that env; a fresh shell without conda activate ./.cuopt_env hits cryptic linker errors.PARALLEL_LEVEL if RAM is constrained — see references/build_and_test.md. The default $(nproc) can OOM mid-build because CUDA compilation needs ~4–8 GB per job.RAPIDS_DATASET_ROOT_DIR../build.sh # Build everything
./build.sh --help # List components: libcuopt, cuopt, cuopt_server, docs
ctest --test-dir cpp/build # C++ tests
pytest -v python/cuopt/cuopt/tests # Python tests
pytest -v python/cuopt_server/tests # Server tests
For component-specific build commands, run-test detail, and PARALLEL_LEVEL configuration, see references/build_and_test.md.
cuOpt tests depend on MPS/data files that are not checked into the repo. A
missing dataset surfaces as a MPS_PARSER_ERROR ... Error opening MPS file
test failure at 0ms — it is not a build or logic failure.
Before running any C++ or Python tests, follow the dataset download and
RAPIDS_DATASET_ROOT_DIR export steps in the repo's CONTRIBUTING.md
("Building for development" section) — that is the canonical list and mapping.
If a test fails with a missing-file error, run the matching download step from
CONTRIBUTING.md and re-run the test. Do not report missing-dataset failures
back to the user as the task outcome.
cuOpt uses Cython to bridge Python and C++. See references/python_bindings.md for the full architecture, parameter flow walkthrough, key files, and Cython patterns.
For pre-commit setup, DCO sign-off (git commit -s), the fork-based PR workflow, the draft-PR rule for agents, PR-description rules (keep it short — no "how it works" walkthroughs or file tables), script and CI/workflow authoring principles (extend existing files before adding new ones; no speculative flags, restated defaults, or silent fallbacks), and step-by-step common-task recipes (adding a solver parameter, dependency, server endpoint, or CUDA kernel), see references/contributing.md.
For C++ naming (snake_case, d_/h_ prefixes, _t suffix), file extensions (.hpp/.cpp/.cu/.cuh and which compiler each uses), include order, Python style, error handling (CUOPT_EXPECTS, RAFT_CUDA_TRY), memory management (RMM patterns, no raw new/delete), and test-impact rules, see references/conventions.md.
For build/test pitfalls (Cython rebuild, OOM, CUDA driver mismatch, missing nvcc) and CI failure diagnostics (style checks, DCO failures, dependency drift), see references/troubleshooting.md.
| Purpose | Location |
|---|---|
| Main build script | build.sh |
| Dependencies | dependencies.yaml |
| C++ formatting | .clang-format |
| Conda environments | conda/environments/ |
| Test data | datasets/ |
| CI scripts | ci/ |
Shell-execution, install, conda-env, and sudo policies are covered by Refusal Rules — Read First at the top of this skill.
When implementing or debugging VRP dimensions (constraints, objectives, forward/backward propagation, combine, local-search deltas), read:
references/vrp_skills.md — architecture contracts, required interfaces, and implementation checklist.Read it before adding a new dimension or changing combine semantics.
When a bug surfaces as wrong-but-plausible solver output (invalid lower bound, unexpectedly large duals, 10× iteration blow-up after a small change) rather than a crash, read:
resources/numerical_debugging.md — methodology for locating catastrophic-cancellation sites, the cancellation patterns endemic to cMIR / flow-cover / MIR-style cut construction, and threshold guidance for numerical guards.Apply the instrument-first, guard-at-the-exact-site workflow it describes before patching — speculative fixes on these symptoms usually miss.