NVIDIA cuOpt™ is an Operations Research optimization API using AI to help developers create complex, real-time fleet routing solutions.
Key features of NVIDIA cuOpt:
Dynamic Rerouting : Rerun models and adjust for changes like down drivers, inoperable vehicles, traffic/weather disruptions, and the addition of new orders—all within SLA time constraints. Route 1,000 packages in 10 seconds instead of 20 minutes (that’s 120X faster), with the same level of accuracy.
World-Record Accuracy : Achieve world-record accuracy with a 2.98% error gap on the Gehring & Homberger benchmark.
Scale Seamlessly : Scale out to 1000s of nodes to facilitate computationally heavy use cases. NVIDIA cuOpt performs better than SOTA solutions to address innovative use cases not otherwise possible today.
This NGC collection contains a containerized version of the cuOpt library that can be run as a Python SDK or RESTful microservice. In addition, a helm chart is made available for Kubernetes based deployments.
Example notebooks and deployment scripts can be found on GitHub : NVIDIA/cuOpt-Resources
NVIDIA also provides a course on the basics of using cuOpt through our Deep Learning Institute platform. Users can work with cuOpt interactively on hardware provided by NVIDIA hosted in the cloud.
Access the course here. Users must have an developer account and be signed in.
By pulling and using the containers or Helm charts, you accept the terms and conditions of this End User License Agreement.