skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: DSDP5 user guide - software for semidefinite programming.

Abstract

DSDP implements the dual-scaling algorithm for semidefinite programming. The source code of this interior-point solver, written entirely in ANSI C, is freely available. The solver can be used as a subroutine library, as a function within the Matlab environment, or as an executable that reads and writes to files. Initiated in 1997, DSDP has developed into an efficient and robust general-purpose solver for semidefinite programming. Although the solver is written with semidefinite programming in mind, it can also be used for linear programming and other constraint cones. The features of DSDP include the following: a robust algorithm with a convergence proof and polynomially bounded complexity under mild assumptions on the data, primal and dual solutions, feasible solutions when they exist or approximate certificates of infeasibility, initial points that can be feasible or infeasible, relatively low memory requirements for an interior-point method, sparse and low-rank data structures, extensibility that allows applications to customize the solver and improve its performance, a subroutine library that enables it to be linked to larger applications, scalable performance for large problems on parallel architectures, and a well-documented interface and examples of its use. The package has been used in many applications and tested for efficiency, robustness,more » and ease of use. We welcome and encourage further use under the terms of the license included in the distribution.« less

Authors:
; ;
Publication Date:
Research Org.:
Argonne National Lab. (ANL), Argonne, IL (United States)
Sponsoring Org.:
USDOE Office of Science (SC)
OSTI Identifier:
947970
Report Number(s):
ANL/MCS-TM-277
TRN: US200906%%107
DOE Contract Number:  
DE-AC02-06CH11357
Resource Type:
Technical Report
Country of Publication:
United States
Language:
ENGLISH
Subject:
99 GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE; ALGORITHMS; CONES; CONVERGENCE; DISTRIBUTION; EFFICIENCY; LINEAR PROGRAMMING; PERFORMANCE; PROGRAMMING

Citation Formats

Benson, S J, Ye, Y, and Mathematics and Computer Science. DSDP5 user guide - software for semidefinite programming.. United States: N. p., 2006. Web. doi:10.2172/947970.
Benson, S J, Ye, Y, & Mathematics and Computer Science. DSDP5 user guide - software for semidefinite programming.. United States. doi:10.2172/947970.
Benson, S J, Ye, Y, and Mathematics and Computer Science. Tue . "DSDP5 user guide - software for semidefinite programming.". United States. doi:10.2172/947970. https://www.osti.gov/servlets/purl/947970.
@article{osti_947970,
title = {DSDP5 user guide - software for semidefinite programming.},
author = {Benson, S J and Ye, Y and Mathematics and Computer Science},
abstractNote = {DSDP implements the dual-scaling algorithm for semidefinite programming. The source code of this interior-point solver, written entirely in ANSI C, is freely available. The solver can be used as a subroutine library, as a function within the Matlab environment, or as an executable that reads and writes to files. Initiated in 1997, DSDP has developed into an efficient and robust general-purpose solver for semidefinite programming. Although the solver is written with semidefinite programming in mind, it can also be used for linear programming and other constraint cones. The features of DSDP include the following: a robust algorithm with a convergence proof and polynomially bounded complexity under mild assumptions on the data, primal and dual solutions, feasible solutions when they exist or approximate certificates of infeasibility, initial points that can be feasible or infeasible, relatively low memory requirements for an interior-point method, sparse and low-rank data structures, extensibility that allows applications to customize the solver and improve its performance, a subroutine library that enables it to be linked to larger applications, scalable performance for large problems on parallel architectures, and a well-documented interface and examples of its use. The package has been used in many applications and tested for efficiency, robustness, and ease of use. We welcome and encourage further use under the terms of the license included in the distribution.},
doi = {10.2172/947970},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Tue Jan 24 00:00:00 EST 2006},
month = {Tue Jan 24 00:00:00 EST 2006}
}

Technical Report:

Save / Share: