Quick Start to GPU-Accelerated Large-Scale Logistics and Supply Chain Optimization with NVIDIA cuOpt

Video Description

Part 2: https://youtu.be/jnDPQeUO0CM?si=w03E6JcLYR_qy276 Part 3: https://youtu.be/kSATyJrELUI Want to get started with GPU-accelerated optimization in minutes? Learn how to quickly install and verify the NVIDIA cuOpt server using NVIDIA Launchable or your own GPU machine. In this short video, Adi Yanovski, Technical Marketing Engineer at NVIDIA, walks you through: • What cuOpt is and how it accelerates linear programming (LP), mixed-integer programming (MIP), and vehicle routing problem (VRP) • How to spin up a GPU-powered environment using NVIDIA Launchable • Step-by-step cuOpt server installation via pip • Running a quick smoke test using a simple vehicle routing example • How cuOpt REST API makes it easy to integrate across languages and systems Ideal for developers and operations researchers tackling fleet management, last-mile delivery, logistics, production planning, or real-time supply chain and portfolio optimization challenges. Try the code: GitHub: https://github.com/NVIDIA/cuopt Explore cuOpt Examples: https://github.com/NVIDIA/cuopt-examples Smoke test used in video: https://docs.nvidia.com/cuopt/user-guide/latest/cuopt-server/quick-start.html#smoke-test Learn more: https://docs.nvidia.com/cuopt/user-guide/latest/introduction.html Launchable GPU Environment: https://brev.nvidia.com/launchable/deploy/now?launchableID=env-2qIG6yjGKDtdMSjXHcuZX12mDNJ Google Colab: https://colab.research.google.com/github/nvidia/cuopt-examples/ 0:00 - 0:21 - Intro to NVIDIA cuOpt 0:22 - 0:50 - Use cases: What cuOpt solves? 0:51 - 2:36 - Installation with NVIDIA Launchable 2:37 - 4:40 - Running a basic optimization example 4:41 - 5:23 - Next steps: Docs, GitHub, production deployment #OperationResearch #AI #OpenSource #NVIDIAcuOpt Open Source, NVIDIA cuOpt