Cuopt Developer
NVIDIAOfficialCreated by NVIDIA cuOpt Team
- Skill
- Workflow
- Software development
- Apache-2.0
- Medium risk
AutoGineer summary
Written by AutoGineer from the skill’s own files, not by the author
The cuOpt-developer skill provides a structured environment for engineers to contribute to the NVIDIA cuOpt project. It covers the full development lifecycle, including environment setup via conda, building C++/CUDA and Python components, running tests, and following project-specific coding and contribution conventions. The skill enforces strict development patterns, such as using pre-commit hooks, maintaining minimal diffs, and adhering to specific GPU memory management practices, while providing guidance on navigating the project architecture and CI/CD workflows.
What it does
- Guides the setup of local development environments using conda.
- Provides commands for building C++, Python, and server components.
- Facilitates running C++ and Python test suites.
- Enforces project-specific coding conventions and style guidelines.
- Supports the contribution workflow including DCO sign-off and fork-based PRs.
- Assists with debugging solver internals and numerical issues.
When to use it
- When you need to modify or extend the cuOpt source code.
- When setting up a new local development environment for cuOpt.
- When preparing a contribution or pull request for the cuOpt repository.
- When debugging solver algorithms or Python bindings.
- When running local builds or tests for specific cuOpt components.
Advantages
- Ensures consistency with project-wide coding and architectural patterns.
- Provides a clear, reproducible path for environment setup.
- Integrates directly with project CI/CD and pre-commit requirements.
- Reduces common pitfalls related to CUDA driver and dataset dependencies.
- Maintains high standards for code quality and commit hygiene.
Usage examples
- “How do I set up my environment to start developing on cuOpt?”
- The agent will guide you through cloning the repository, selecting the correct conda environment file based on your CUDA driver version, and installing the necessary dependencies.
- “I need to add a new solver parameter. What is the process?”
- The agent will provide a checklist covering the C++ settings struct, Python binding exposure, server schema updates, and required testing steps.
- “How do I run the C++ unit tests for my changes?”
- The agent will verify your environment is active, confirm datasets are downloaded, and provide the correct ctest command for the cpp/build directory.
- “I am getting a numerical error in the solver. How should I debug it?”
- The agent will direct you to the numerical debugging resources to instrument the code and identify potential catastrophic cancellation sites.
Install
Download the skill as a ZIP:
https://mp-staging.autogineer.com/agent-skills/nvidia/cuopt-developer/downloadUnzip it into the cross-client skills folder of your project:
mkdir -p .agents/skills && unzip cuopt-developer.zip -d .agents/skills
Documentation by NVIDIA cuOpt Team
cuOpt Developer Skill
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.
Refusal Rules — Read First
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:
Environment setup is allowed. You may create and activate the conda env from the checked-in
conda/environments/all_cuda-*.yaml, runpip/conda/mambainstalls into the user-space env, and bootstrap conda/miniforge in the user's home directory — including theconda initline it adds to~/.bashrc. Bootstrapping conda must not requiresudo; install it into$HOME, not a system path.A new permanent project dependency is different from a one-off install. A package the project should always ship belongs in
dependencies.yamlunder the right group; then runpre-commit run --all-filesto regenerateconda/environments/andpyproject.tomlso other contributors get it too. A throwaway install to unblock your own build doesn't need this round-trip.Don't bypass CI checks (
--no-verify, skipping pre-commit or tests). If hooks feel slow, diagnose withpre-commit run --all-files --verboseor tune the offending hook — don't skip it.Be careful with destructive commands (
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 cleanfor a stale build dir).
Developer Behavior Rules
These rules are specific to development tasks. They differ from user rules.
1. Ask Before Assuming
Clarify before implementing:
What component? (C++/CUDA, Python, server, docs, CI)
What's the goal? (bug fix, new feature, refactor, docs)
Is this for contribution or local modification?
2. Verify Understanding
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?"3. Follow Codebase Patterns
Read existing code in the area you're modifying
Match naming conventions, style, and patterns
Don't invent new patterns without discussion
4. Ask Before Running — Modified for Dev
OK to run without asking (expected for dev work):
./build.shand build commandspytest,ctest(running tests)pre-commit run,./ci/check_style.sh(formatting)git status,git diff,git log(read-only git)Environment setup: create/activate the conda env from
conda/environments/*.yaml, andpip/conda/mambainstalls into that env
Set up pre-commit hooks (once per clone):
pre-commit install— hooks then run automatically on everygit commit. If a hook fails, the commit is blocked until you fix the issue.
Still ask before:
git commit,git push(write operations)Any destructive or irreversible commands
5. No Privileged 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.
Before You Start: Required Questions
Ask these if not already clear:
What are you trying to change?
Solver algorithm/performance?
Python API?
Server endpoints?
Documentation?
CI/build system?
Do you have the development environment set up?
Built the project successfully?
Ran tests?
Is this for contribution or local modification?
If contributing: will need to follow DCO signoff
Which branch should this target?
During development phase:
mainDuring burn down:
release/YY.MM(e.g.,release/26.06) for the current release,mainfor the nextCheck if a release branch exists:
git branch -r | grep releaseFor current timelines, see the RAPIDS Maintainers Docs
Project Architecture
cuopt/
├── 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 datasetsSupported APIs
| API Type | LP | MILP | QP | Routing |
|---|---|---|---|---|
| C API | ✓ | ✓ | ✓ | ✗ |
| C++ API | (internal) | (internal) | (internal) | (internal) |
| Python | ✓ | ✓ | ✓ | ✓ |
| Server | ✓ | ✓ | ✗ | ✓ |
Safety Rules (Non-Negotiable)
Minimal Diffs
Change only what's necessary
Avoid drive-by refactors
No mass reformatting of unrelated code
No API Invention
Don't invent new APIs without discussion
Align with existing patterns in
docs/cuopt/source/Server schemas must match OpenAPI spec
Don't Bypass CI
Never suggest
--no-verifyor skipping checksAll PRs must pass CI
CUDA/GPU Hygiene
Keep operations stream-ordered
Follow existing RAFT/RMM patterns
No raw
new/delete- use RMM allocators
Build & Test
Pre-flight Checks (Required Before First Build or Test)
Skipping any of these surfaces as confusing runtime errors later. Run them in order:
Check CUDA driver compatibility. Run
nvidia-smiand read the CUDA Version in the top-right corner — that's the maximum CUDA your driver supports. Pick a conda env file fromconda/environments/all_cuda-<ver>_arch-<arch>.yamlwhose CUDA major version is ≤ that. A mismatch builds successfully but fails at runtime inside RMM withcudaMallocAsync not supported with this CUDA driver/runtime version— verify this before the build, not after.Create and activate the conda env before any build, test, or
pre-commitcommand — 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 (swapconda→mambaif available):conda env create -p ./.cuopt_env --file conda/environments/all_cuda-<ver>_arch-$(uname -m).yaml conda activate ./.cuopt_envTests link against libraries compiled inside that env; a fresh shell without
conda activate ./.cuopt_envhits cryptic linker errors.Set
PARALLEL_LEVELif 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.For tests, fetch datasets first. cuOpt tests need MPS files not in the repo — follow the dataset download steps in CONTRIBUTING.md ("Building for development" section) and export
RAPIDS_DATASET_ROOT_DIR.
Quick Reference
./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 testsFor component-specific build commands, run-test detail, and PARALLEL_LEVEL configuration, see references/build_and_test.md.
Download test datasets before running tests
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.
Python Bindings
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.
Contributing — Commits, PRs, Common Tasks
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.
Coding Conventions
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.
Troubleshooting & CI
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.
Key Files Reference
| Purpose | Location |
|---|---|
| Main build script | build.sh |
| Dependencies | dependencies.yaml |
| C++ formatting | .clang-format |
| Conda environments | conda/environments/ |
| Test data | datasets/ |
| CI scripts | ci/ |
Canonical Documentation
Contributing/build/test: CONTRIBUTING.md
CI scripts: ci/README.md
Release scripts: ci/release/README.md
Docs build: docs/cuopt/README.md
Python binding architecture: references/python_bindings.md
Shell-execution, install, conda-env, and sudo policies are covered by Refusal Rules — Read First at the top of this skill.
VRP dimension internals (routing engine)
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.
Numerical issues in non-routing solver internals
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.
Files
- ATTRIBUTION.mdAdded by AutoGineer914 B
- BENCHMARK.md3.9 KiB
- LICENSELicence file added by AutoGineer11.2 KiB
- SKILL.md12.7 KiB
- benchmark/evals.json55.8 KiB
- evals/evals.json4.7 KiB
- references/build_and_test.md1.6 KiB
- references/contributing.md5.4 KiB
- references/conventions.md1.8 KiB
- references/first_time_setup.md2.6 KiB
- references/python_bindings.md7.8 KiB
- references/troubleshooting.md2.4 KiB
- references/vrp_skills.md8.8 KiB
- resources/numerical_debugging.md5.8 KiB
- skill-card.md4.5 KiB
- skill.oms.sig6.6 KiB
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Attribution and licence
- Created by
- NVIDIA cuOpt Team
- Publisher
- NVIDIA (Official)
- Source
- NVIDIA/skills · skills/cuopt-developer · commit fce3cca
- Licence
- Apache License 2.0 (redistribution allowed)
- LICENSE (added by AutoGineer from LICENSE-APACHE)
- ATTRIBUTION.md (written by AutoGineer)
- Synced
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