The NEOS Server offers CSDP (version 6.0.1) for the solution of semidefinite
programming problems in
sparse SDPA format or in
CSDP is a library of routines that implements a predictor corrector variant
of the semidefinite programming algorithm of Helmberg, Rendl, Vanderbei,
and Wolkowicz. The main advantages of this code are that it is written
to be used as a callable subroutine, it is written in C for efficiency
and portability, and it makes effective use of sparsity in the constraint
matrices. The code is designed to make use of highly optimized linear
algebra routines from the LAPACK and ATLAS-BLAS libraries.
Source code, binaries, and documentation are available from
CSDP was developed by
This solver was implemented by
Hans Mittelmann and executes at
Using the NEOS Server for CSDP
The user must submit a model in either sparse SDPA or SeDuMi Matlab
format to solve a semidefinite programming problem.
Note that when submitting via e-mail or XML-RPC empty tokens need
to be deleted.
Examples of models in sparse SDPA format can be found in the
The same problems in SeDuMi format are
here. Other files in this format are at
7th DIMACS Challenge library.
An initial solution to the problem may also be supplied.
In addition to CSDP's own error output the 6 error measures are printed
according to the DIMACS 7th Challenge, see the
This facilitates comparison with other SDP solvers.