https://github.com/kul-optec/superscs
Fast conic optimization in C
Science Score: 10.0%
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○codemeta.json file
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✓Academic publication links
Links to: arxiv.org -
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○Scientific vocabulary similarity
Low similarity (12.4%) to scientific vocabulary
Keywords
conic-programs
convex-optimization
numerical-optimization
Last synced: 4 months ago
·
JSON representation
Repository
Fast conic optimization in C
Basic Info
- Host: GitHub
- Owner: kul-optec
- License: other
- Language: C
- Default Branch: master
- Homepage: https://kul-forbes.github.io/scs/
- Size: 51.1 MB
Statistics
- Stars: 27
- Watchers: 9
- Forks: 10
- Open Issues: 10
- Releases: 0
Fork of cvxgrp/scs
Topics
conic-programs
convex-optimization
numerical-optimization
Created almost 9 years ago
· Last pushed over 4 years ago
https://github.com/kul-optec/superscs/blob/master/
SuperSCS
====
[](https://www.codacy.com/app/alphaville/scs?utm_source=github.com&utm_medium=referral&utm_content=kul-forbes/scs&utm_campaign=badger)
[](https://travis-ci.org/kul-optec/scs)
[](https://ci.appveyor.com/project/alphaville/scs/branch/master)
[](https://codecov.io/gh/kul-optec/scs)
[](https://gitter.im/kul-forbes/scs?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge)
[](https://opensource.org/licenses/MIT)
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**.
### Documentation
Detailed documentation can be found [**here**](https://kul-optec.github.io/superscs).
### Download
Download the [**current stable version**](https://github.com/kul-optec/superscs/archive/master.zip)
Check out the [**installation instructions**](https://kul-optec.github.io/superscs/page_installation.html)
### Docker
It is straightforward to download and run the [SuperSCS docker image](https://hub.docker.com/r/kulforbes/superscs/).
Simply run:
```
docker pull kulforbes/superscs
docker run -it kulforbes/superscs
```
Find out [**more information here**](https://kul-optec.github.io/superscs/page_installation.html).
### Supported Interfaces
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**](https://kul-optec.github.io/superscs/page_installation.html) for further information.
### Cite SuperSCS
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](https://arxiv.org/abs/1609.06955), 2017.
Cite the software as follows:
```
@MISC{superscs,
AUTHOR = {Sopasakis, P. and Menounou, K. and Patrinos, P.},
HOWPUBLISHED = {\url{https://kul-optec.github.io/scs/}},
MONTH = {Apr},
TITLE = {{SuperSCS}: A fast and accurate conic optimization solver},
YEAR = {2017},
}
```
Owner
- Name: OPTEC
- Login: kul-optec
- Kind: organization
- Repositories: 24
- Profile: https://github.com/kul-optec
KU Leuven Center of Excellence: Optimization in Engineering
GitHub Events
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- Watch event: 1
Last Year
- Watch event: 1