OSQP uses a specialized ADMM-based first-order method with custom sparse linear algebra routines that exploit structure in problem data. The algorithm is absolutely division-free after the setup and it requires no assumptions on problem data (the problem only needs to be convex). It just works. OSQP has an easy interface to generate customized embeddable C code with no memory manager required. OSQP supports many interfaces including C/C++, Fortran, Matlab, Python, R, Julia, Rust.

Features

  • Library-free
  • Many interfaces
  • Embeddable
  • Documentation available
  • Examples available
  • OSQP is free

Project Samples

Project Activity

See All Activity >

Categories

Machine Learning

License

Apache License V2.0

Follow The Operator Splitting QP Solver

The Operator Splitting QP Solver Web Site

Other Useful Business Software
Host LLMs in Production With On-Demand GPUs Icon
Host LLMs in Production With On-Demand GPUs

NVIDIA L4 GPUs. 5-second cold starts. Scale to zero when idle.

Deploy your model, get an endpoint, pay only for compute time. No GPU provisioning or infrastructure management required.
Try Free
Rate This Project
Login To Rate This Project

User Reviews

Be the first to post a review of The Operator Splitting QP Solver!

Additional Project Details

Operating Systems

Linux, Mac, Windows

Programming Language

C

Related Categories

C Machine Learning Software

Registered

2024-08-15