2011 Fiscal Year Final Research Report
A parallel implementation for solving large-scale Semidefinite Programs having sparse Schur complement matrix
| Project/Area Number |
21710148
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| Research Category |
Grant-in-Aid for Young Scientists (B)
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| Allocation Type | Single-year Grants |
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| Research Field |
Social systems engineering/Safety system
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| Research Institution | Tokyo Institute of Technology |
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Principal Investigator |
YAMASHITA Makoto 東京工業大学, 大学院・情報理工学研究科, 助教 (20386824)
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| Project Period (FY) |
2009 – 2011
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| Keywords | 応用数学 / ハイパフォーマンスコンピューティング / 数理最適化 / 並列計算 / 半正定値計画問題 |
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| Research Abstract |
The reduction in computation time for solving Semidefinite Programs is essential to many applications like sensor network localization problems and polynomial optimizations. We focus on the sparsity of the Schur complement matrix, which occupies most computation time. We estimate the computation cost of each element of the matrix and propose efficient parallel schemes. From numerical results, we verified that the parallel schemes successfully reduce the computation time.
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[Book] Latest developments in the SDPA Family for solving large-scale SDPs,inHandbook on Semidefinite, Cone and Polynomial Optimization : Theory, Algorithms, Software and Applicationsedited by Miguel F. Anjos and Jean B. Lasserre2011
Author(s)
Makoto Yamashita, Katsuki Fujisawa, Mituhiro Fukuda, Kazuhiro Kobayashi, Kazuhide Nakta, Maho Nakata
Total Pages
687-714
Publisher
Springer, NY, USA
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