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<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE pkgmetadata SYSTEM "">
<maintainer type="project">
<name>Gentoo Science Project</name>
<longdescription lang="en">
The DSDP software 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. 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.