SuperSCS  1.3.2
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SuperSCS: Fast & Accurate conic programming

About SuperSCS

SuperSCS is a fast solver for conic problems of the form

\begin{eqnarray*} &&\mathrm{Minimize}\ c' x \\ &&Ax + s = b\\ &&s\in\mathcal{K}, \end{eqnarray*}

where \(A\in\mathbb{R}^{m\times n}\) is a (sparse) matrix, and \(\mathcal{K}\) is a closed, convex, proper cone.

\(\mathcal{K}\) can be the Cartesian product of the zero cone, the positive orthant, the second-order cone, the positive semidefinite cone and many other.

SuperSCS is based on the algorithmic scheme SuperMann applied to a Douglas-Rachford splitting on the self-dual homogeneous embedding of the original problem.

SuperSCS achieves higher accuracy and faster convergence compared to SCS as you can see for example in the CVX examples page.


  1. Installation
  2. Documentation
  3. Performance
  4. Under the hood


The source code of SuperSCS is available on github.

Check out the installation guide.


Quality assurance:


SuperSCS is an open-source project to which you may contribute.

Before contributing or filing an issue, please read this guide.


SuperSCS is licensed with an MIT license.

The MIT license is a short and simple permissive license with conditions only requiring preservation of copyright and license notices.

Licensed works, modifications, and larger works may be distributed under different terms and without source code.

You only need to keep LICENSE.txt and, if you redistribute the source code, the copyright notices therein.

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Cite SuperSCS

SuperSCS is based on the algorithmic scheme presented in:

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