Skip to main content

cuopt-install

Install cuOpt for Python, C, or server via pip, conda, or Docker; verify the install. For building cuOpt from source, see cuopt-developer.

Quellinformationen

Repository
NVIDIA/cuopt
Letzte Quellaktivität
15. Oktober 2026 um 22:08
Erkannte Sprache von SKILL.md
Englisch
Sterne
1.092
Forks
249

Installationsoptionen

Standardmäßig ist der Prompt ausgewählt, der zuerst die Quelle prüft. Sie können zu einem direkten Befehl wechseln oder eine lokale Kopie herunterladen.

Quelldateien prüfen

Lesen Sie SKILL.md und alle von SkillsMP angezeigten Begleitdateien, bevor Sie sich für eine Installation entscheiden.

Datei-Explorer
7 Dateien

SKILL.md wird angezeigt

SKILL.md
Quellanweisungen · Schreibgeschützte Vorschau
name
cuopt-install
version
26.12.00
description
Install cuOpt for Python, C, or server via pip, conda, or Docker; verify the install. For building cuOpt from source, see cuopt-developer.
license
Apache-2.0
metadata
{"author":"NVIDIA cuOpt Team","tags":["cuopt","install","deployment","python","server"]}
# cuOpt Install (user) Install cuOpt to *use* it from Python, C, or as a REST server. For building cuOpt from source to contribute or modify it, see `cuopt-developer`. ## System requirements - **GPU**: NVIDIA Compute Capability ≥ 7.0 (Volta or newer). Examples: V100, A100, H100, RTX 20xx/30xx/40xx. Not supported: GTX 10xx (Pascal). - **CUDA**: 12.x or 13.x. The package CUDA suffix must match the runtime CUDA (e.g. `cuopt-cu12` / `libcuopt-cu12` with CUDA 12). - **Driver**: NVIDIA driver compatible with the CUDA version. - `cuopt-cuXX` (Python) depends on `libcuopt-cuXX` (C), so installing the Python package also installs the C library and headers. Installing `libcuopt-cuXX` on its own does **not** install the Python API. ## Required questions Ask these if not already clear: 1. **Interface** — Python, C, or REST server? Server can be called from any language via HTTP. 2. **CUDA version** — What is installed? Check with `nvcc --version` or `nvidia-smi`. 3. **Package manager** — pip, conda, or Docker preferred? 4. **Release channel** — latest stable release (default) or nightly (built from the development branch, may be unstable)? 5. **Environment** — Local machine with GPU, cloud instance, Docker/Kubernetes, or remote/server (no local GPU)? ## Release channels Commands below install the **latest stable release**. For **nightly** builds (development branch HEAD, version `NEXT` = `VERSION` file on `main`, e.g. `26.12`), change: - **pip**: add `--pre --extra-index-url=https://pypi.anaconda.org/rapidsai-wheels-nightly/simple/` and pin each listed cuOpt package (including `cuopt-sh-client`) to `==NEXT.*`. - **conda**: replace `-c rapidsai` with `-c rapidsai-nightly` and pin `=NEXT.*`. - **Docker**: use `nvidia/cuopt:NEXT.0a-cu12` / `-cu13` / `-cu13-ubi10` instead of `latest-*`. ## Python API **Choose one** — do not run both. The second install would override the first and can cause CUDA / package mismatch. ### pip - **CUDA 13.x:** ```bash pip install --extra-index-url=https://pypi.nvidia.com cuopt-cu13 ``` - **CUDA 12.x:** ```bash pip install --extra-index-url=https://pypi.nvidia.com cuopt-cu12 ``` ### conda ```bash conda install -c rapidsai -c conda-forge -c nvidia cuopt ``` ### Verify ```python import cuopt print(cuopt.__version__) from cuopt import routing dm = routing.DataModel(n_locations=3, n_fleet=1, n_orders=2) ``` ## C API The C API ships in `libcuopt-cuXX`, which is also pulled in as a dependency of `cuopt-cuXX` — so if you already installed the Python package, the C library and headers are already present. Install `libcuopt` standalone only when you want the C API without Python. **Choose one** of pip or conda — do not run both. ### pip - **CUDA 13.x:** ```bash pip install --extra-index-url=https://pypi.nvidia.com libcuopt-cu13 ``` - **CUDA 12.x:** ```bash pip install --extra-index-url=https://pypi.nvidia.com libcuopt-cu12 ``` ### conda ```bash conda install -c rapidsai -c conda-forge -c nvidia libcuopt ``` ### Verify See [`references/verification_examples.md`](references/verification_examples.md) for the canonical C-API header/library `find` commands (conda and pip/venv variants). ## Server (REST) ### pip ```bash pip install --extra-index-url=https://pypi.nvidia.com cuopt-server-cu12 cuopt-sh-client ``` ### conda ```bash conda install -c rapidsai -c conda-forge -c nvidia cuopt-server cuopt-sh-client ``` ### Docker ```bash docker pull nvidia/cuopt:latest-cu12 docker run --gpus all -it --rm -p 8000:8000 nvidia/cuopt:latest-cu12 ``` ### Verify ```bash python -m cuopt_server.cuopt_service --ip 0.0.0.0 --port 8000 & sleep 5 curl -s http://localhost:8000/cuopt/health | jq . ``` ## Common Issues - `No module named 'cuopt'` → check `pip list | grep cuopt`, `which python`, reinstall with the correct extra-index-url. - CUDA not available → run `nvidia-smi` and `nvcc --version`; ensure the package CUDA suffix (`cu12` vs `cu13`) matches the installed CUDA. - Python vs C → `cuopt-cuXX` pulls in `libcuopt-cuXX` as a transitive dependency, so the C library (`libcuopt.so`) and headers (`cuopt_c.h`) are already available after installing the Python package. The reverse is **not** true: `libcuopt-cuXX` alone does not install the Python bindings. ## See also - [verification_examples.md](references/verification_examples.md) — full verification recipes for Python, C, server, and Docker. - `cuopt-developer` — build cuOpt from source and contribute to the codebase.
Auf GitHub ansehen