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

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Categories

Machine Learning

License

Apache License V2.0

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Additional Project Details

Operating Systems

Linux, Mac, Windows

Programming Language

C

Related Categories

C Machine Learning Software

Registered

2024-08-15