Search results

• NVIDIA

  Downloadable

  cuopt

  World-record accuracy and performance for complex route optimization.

  Model
• 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.

  Skill
• cuopt-developer

  Modify, build, test, debug, and contribute to NVIDIA cuOpt (C++/CUDA, Python, server, CI). Use for solver internals, PRs, DCO, and code conventions.

  Skill
• cuopt-numerical-optimization-api

  LP, MILP, and QP (beta) with cuOpt — Python, C, and CLI. Use when the user is solving LP, MILP, or QP with any cuOpt interface.

  Skill
• cuopt-multi-objective-exploration

  Trace, complete, and interpret the Pareto frontier across competing objectives using repeated single-objective cuOpt solves (weighted-sum and ε-constraint).

  Skill
• cuopt-routing-api-python

  Vehicle routing (VRP, TSP, PDP) with cuOpt — Python API only. Use when the user is building or solving routing in Python.

  Skill
• cuopt-server-api-python

  cuOpt REST server — start server, endpoints, Python/curl client examples. Use when the user is deploying or calling the REST API.

  Skill
• cuopt-numerical-optimization-formulation

  LP, MILP, QP — concepts, problem-text parsing, and formulation patterns (parameters, constraints, decisions, objective). Concepts only; no API.

  Skill
• Financial Services

  LaunchableDeveloper Example

  Quantitative Portfolio Optimization

  Enable fast, scalable, and real-time portfolio optimization for financial institutions.

  Blueprint
• Playbooks

  20 MIN

  Portfolio Optimization

  GPU-Accelerated portfolio optimization using cuOpt and cuML

  Playbook
• portfolio-optimization

  Use when a user asks to build, optimize, backtest, rebalance, or analyze a stock portfolio with Mean-CVaR, Mean-Variance/SOCP variance caps, efficient frontiers, scenario generation, or NVIDIA cuOpt.

  Skill