Parallel Computing on Semidefinite Programs
Parallel Computing on Semidefinite Programs
复制标题
半定程序的并行计算
DOI：
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复制
发表时间：
2003
期刊：
影响因子：
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通讯作者：
S. Benson
中科院分区：
文献类型：
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作者：
S. Benson
本文演示了内部方法如何有效地使用多个处理器来求解VLSI设计，控制理论和图形着色中出现的大型半决赛程序。这些方法的先前实现仅限于单个处理器。通过计算和求解Schur补体矩阵并联，多个处理器可以更快地解决中和大问题的解决方案。用于半决赛编程的双缩放算法适用于分布式的新兴环境，用于解决培养基和大问题的速度比通过内部点算法更快地解决的媒介和大问题。确定了影响求解器并行可伸缩性的三个标准。数值结果表明，在适当的大小和结构的问题上，内点方法的实现在并行体系结构上表现出良好的可扩展性。
This paper demonstrates how interior-point methods can use multiple processors efficiently to solve large semidefinite programs that arise in VLSI design, control theory, and graph coloring. Previous implementations of these methods have been restricted to a single processor. By computing and solving the Schur complement matrix in parallel, multiple processors enable the faster solution of medium and large problems. The dual-scaling algorithm for semidefinite programming was adapted to a distributedmemory environment and used to solve medium and large problems than faster than could previously be solved by interior-point algorithms. Three criteria that influence the parallel scalability of the solver are identified. Numerical results show that on problems of appropriate size and structure, the implementation of an interior-point method exhibits good scalability on parallel architectures.
SDPA（半定规划算法）的新特性
DOI：
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发表时间：
2007
期刊：
影响因子：
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作者：
Kazuhide Nakata;Katsuki Fujisawa;Mituhiro Fukuda;Kazuhiro Kobayashi;Masakazu Kojima;Maho Nakata;and Makoto Yamashita
通讯作者：
and Makoto Yamashita