Parallel implementation of a semidefinite programming solver based on CSDP on a distributed memory cluster

In this paper, we present the algorithmic framework and practical aspects of implementing a parallel version of a primal-dual semidefinite programming solver on a distributed memory computer cluster. Our implementation is based on the CSDP solver and uses a message passing interface and the ScaLAPAC...

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Bibliographic Details
Published inOptimization methods & software Vol. 25; no. 3; pp. 405 - 420
Main Authors Ivanov, I. D., de Klerk, E.
Format Journal Article
LanguageEnglish
Published Abingdon Taylor & Francis 01.06.2010
Taylor & Francis Ltd
Subjects
Algorithms
distributed memory cluster
interior-point methods
parallel computing
Semidefinite programming
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Summary:In this paper, we present the algorithmic framework and practical aspects of implementing a parallel version of a primal-dual semidefinite programming solver on a distributed memory computer cluster. Our implementation is based on the CSDP solver and uses a message passing interface and the ScaLAPACK library. A new feature is implemented to deal with problems that have rank-one constraint matrices. We show that significant improvement is obtained for a test set of problems with rank-one constraint matrices. Moreover, we show that very good parallel efficiency is obtained for large-scale problems where the number of linear equality constraints is very large compared to the block sizes of the positive semidefinite matrix variables.
ISSN:1055-6788
1029-4937
DOI:10.1080/10556780903239360