SuperSCS is is a fast and accurate solver for conic optimization problems, that is, problems of the form

minimize        c'x
subject to      Ax + s = b
                s in K

where K is a nonempty, closed, convex cone.

It can be accessed from MATLAB and Python, directly, or via CVX/CVXPy.

Detailed documentation can be found here.

Download the current stable version

Check out the installation instructions

It is straightforward to download and run the SuperSCS docker image.

Simply run:

docker pull kulforbes/superscs
docker run -it kulforbes/superscs

Find out more information here.

SuperSCS can be used in the following ways

• Using the SuperSCS C library
• in MATLAB
  • directly
  • via CVX
• in Python
  • directly
  • via CVXPy

Read the documentation for further information.

SuperSCS is based on the SuperMann algorithmic scheme; plese, cite as follows:

A. Themelis and P. Patrinos, "SuperMann: a superlinearly convergent algorithm for finding fixed points of nonexpansive operators," arXiv:1609.06955, 2017.

Cite the software as follows:

@MISC{superscs,
  AUTHOR       = {Sopasakis, P. and Menounou, K. and Patrinos, P.},
  HOWPUBLISHED = {\url{https://kul-forbes.github.io/scs/}},
  MONTH        = {Apr},
  TITLE        = {{SuperSCS}: A fast and accurate conic optimization solver},
  YEAR         = {2017},
}