# DSDP

[DSDP](https://www.mcs.anl.gov/hs/software/DSDP/) is a free open source
implementation of an interior-point method for semidefinite programming.  It
provides primal and dual solutions, exploits low-rank structure and sparsity
in the data, and has relatively low memory requirements for an interior-point
method.  It allows feasible and infeasible starting points and provides
approximate certificates of infeasibility when no feasible solution exists.
The dual-scaling algorithm implemented in this package has a convergence proof
and worst-case polynomial complexity under mild assumptions on the data.  The
software can be used as a set of subroutines, through Matlab, or by reading
and writing to data files.  Furthermore, the solver offers scalable parallel
performance for large problems and a well documented interface.  Some of the
most popular applications of semidefinite programming and linear matrix
inequalities (LMI) are model control, truss topology design, and semidefinite
relaxations of combinatorial and global optimization problems.