Latest Developments in the SDPA Family for Solving Large-Scale SDPs

Makoto Yamashita (), Katsuki Fujisawa (), Mituhiro Fukuda (), Kazuhiro Kobayashi (), Kazuhide Nakata () and Maho Nakata ()
Additional contact information
Makoto Yamashita: Tokyo Institute of Technology
Katsuki Fujisawa: Chuo University
Mituhiro Fukuda: Tokyo Institute of Technology
Kazuhiro Kobayashi: National Maritime Research Institute
Kazuhide Nakata: Tokyo Institute of Technology
Maho Nakata: RIKEN

Chapter Chapter 24 in Handbook on Semidefinite, Conic and Polynomial Optimization, 2012, pp 687-713 from Springer

Abstract: Abstract The main purpose of this chapter is to introduce the latest developments in SDPA and its family. SDPA is designed to solve large-scale SemiDefinite Programs (SDPs) faster and over the course of 15 years of development, it has been expanded into a high-performance-oriented software package. We hope that this introduction to the latest developments of the SDPA Family will be beneficial to readers who wish to understand the inside of state-of-art software packages for solving SDPs.

Keywords: Memory Space; Element Component; Cholesky Factorization; Chordal Graph; Structural Sparsity (search for similar items in EconPapers)
Date: 2012
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DOI: 10.1007/978-1-4614-0769-0_24

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