NVIDIA/cuopt-examples

Letzte erfasste Quellaktivität: 29. Juli 2026 um 18:35

SkillsMP-Katalog aktualisiert: 5. November 2026 um 19:57

gesammelte Skills: 8

GitHub-Stars: 472
GitHub-Forks: 91

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# cuOpt Examples NVIDIA® cuOpt™ is an open-source GPU-accelerated engine for solving complex decision optimization problems, such as Mixed Integer Programming, Linear Programming, and Vehicle Routing problems. This repository contains a collection of examples demonstrating the use of NVIDIA cuOpt via service APIs, SDK, and Integration with other OSS optimization packages. This repository is under [Apache 2.0 License](LICENSE.md) [cuOpt Docs](https://docs.nvidia.com/cuopt/) ## Quick Start with Docker The easiest way to get started with these examples is using cuOpt docker image. ### Prerequisites - [Docker](https://docs.nvidia.com/ai-enterprise/deployment/vmware/latest/docker.html) - [NVIDIA Container Toolkit](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html#installing-the-nvidia-container-toolkit) - NVIDIA GPU with appropriate drivers ## Requirements For detailed system requirements, please refer to the [NVIDIA cuOpt System Requirements documentation](https://docs.nvidia.com/cuopt/user-guide/latest/system-requirements.html#). Specific requirements are listed in each workflow's README.md and in the root directory's requirements.txt files. ### Running the Examples 1. Clone this repository: ```bash git clone https://github.com/NVIDIA/cuopt-examples.git cd cuopt-examples ``` 2. Pull the cuOpt docker image: For cuda-13: ```bash docker pull nvidia/cuopt:latest-cu13 # To pin to a specific release: docker pull nvidia/cuopt:26.8.0-cu13 ``` For cuda-12: ```bash docker pull nvidia/cuopt:latest-cu12 # To pin to a specific release: docker pull nvidia/cuopt:26.8.0-cu12 ``` 3. Run the examples: For cuda-13: ```bash docker run -it --rm --gpus all --network=host -v $(pwd):/workspace -w /workspace nvidia/cuopt:latest-cu13 /bin/bash -c "pip install -r requirements.txt; jupyter-notebook" ``` For cuda-12: ```bash docker run -it --rm --gpus all --network=host -v $(pwd):/workspace -w /workspace nvidia/cuopt:latest-cu12 /bin/bash -c "pip install -r requirements.txt; jupyter-notebook" ``` 4. Open your browser with the link provided in the terminal, and you can see the notebooks. ## Note These notebooks have been tested on [NVIDIA Launchable](https://brev.nvidia.com/launchable/deploy?launchableID=env-2qIG6yjGKDtdMSjXHcuZX12mDNJ), [Google Colab](https://colab.research.google.com/github/NVIDIA/cuopt-examples/blob/cuopt_examples_launcher/cuopt_examples_launcher.ipynb), and local Jupyter environments. They may work on other platforms as well. ## Repository Structure The repository is organized by use cases, with each directory containing examples and implementations specific to that use case. Each use case directory includes: - Example notebooks - README.md with specific instructions ## Featured Examples ### Intra-Factory Transport Optimization The `intra-factory_transport` directory contains an example of using the cuOpt SDK API to solve a Capacitated Pickup and Delivery Problem with Time Windows (CPDPTW) for optimizing routes of Autonomous Mobile Robots (AMRs) within a factory environment. ## Contributing We welcome contributions! Please see our [CONTRIBUTING.md](CONTRIBUTING.md) file for guidelines on how to contribute new examples or improve existing ones. ## Tutorial Videos [Example videos](https://docs.nvidia.com/cuopt/user-guide/latest/resources.html#cuopt-examples-and-tutorials-videos) can be found listed in the documentation

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Skills in diesem Repository

Datenwissenschaftler Softwareentwickler

2 Berufskategorien · 100% klassifiziert

Skill

Beruf

Beschreibung

Aktualisiert

cuopt-model-mapper

Datenwissenschaftler

Map interpreted optimization problems into cuOpt-native models for the fast path with minimal clarifying questions.

Quellsprache: Englisch

2026-07-29

cuopt-sandbox

Datenwissenschaftler

Run cuOpt in the NemoClaw sandbox — probe/smoke gates, prefer cancelable Python gRPC jobs, use legacy remote execution only when that API is unavailable, then vendored cuOpt skills.

Quellsprache: Englisch

2026-07-29

optimization-mode-router

Datenwissenschaftler

Choose fast direct-to-cuOpt solve versus replayable or auditable model artifact mode.

Quellsprache: Englisch

2026-07-29

tabular-optimization-ingestion

Datenwissenschaftler

Infer optimization structure from uploaded tables and identify minimal clarifications before cuOpt modeling.

Quellsprache: Englisch

2026-07-29

cuopt-debugging

Softwareentwickler

Troubleshoot cuOpt LP/MILP problems including errors, wrong results, infeasible solutions, performance issues, and status codes. Use when the user says something isn't working, gets unexpected results, or needs help diagnosing issues.

Quellsprache: Englisch

2026-07-20

optimization-from-data-orchestrator

Softwareentwickler

Coordinate uploaded data plus a natural-language question into interpretation, clarification, cuOpt solve, and a user-facing answer.

Quellsprache: Englisch

2026-06-24

optimization-intent-router

Softwareentwickler

Classify whether a data-backed request is LP, MILP, QP, routing, or non-optimization analytics.

Quellsprache: Englisch

2026-06-24

generic-max-supply

Softwareentwickler

Multi-period supply chain planning model: data files, BOM structure, variable/constraint reference for the max-supply base model.

Quellsprache: Englisch

2026-03-12

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