cuOpt

cuOpt is a GPU-accelerated decision optimization library developed by NVIDIA. The library is designed to solve large optimization problems such as logistics planning, routing, and resource allocation. It uses the parallel processing capabilities of NVIDIA GPUs to reduce solution times for workloads that are often too slow on CPU-only systems.

cuOpt focuses on optimization domains such as linear programming, mixed-integer programming, and vehicle routing problems. These problem types are common in supply chains, transportation systems, manufacturing, energy planning, and financial modeling. The library can process very large numbers of variables and constraints while still producing results fast enough for operational decision-making.

NVIDIA provides cuOpt with GPU-accelerated barrier methods and heuristics. This allows the library to support both exact optimization workflows and faster approximate methods when a system needs quick answers. cuOpt can also recompute solutions as inputs change, which is useful for dynamic routing, scheduling, and other near real-time applications.

cuOpt integrates with tools such as AMPL, CVXPY, Pyomo, PuLP, and SciPy. This makes it possible to adapt existing optimization models without rebuilding an entire workflow from scratch. The library can run as a standalone solver or as part of a larger application that combines simulation, automation, and machine learning.

SwissGPU provides dedicated NVIDIA GPU workstations hosted on bare metal. This infrastructure is well suited for cuOpt workloads that need reliable access to GPU compute resources. You can install cuOpt in a CUDA-based software environment and run optimization tasks such as route planning, scheduling, or resource allocation directly on the workstation.

Resources

SwissGPU