Solving large-scale semidefinite programs in parallel

被引：8
|
作者：
Nayakkankuppam, Madhu V. [1 ]
机构：
[1] Bloomberg LP, Computat Finance Grp, New York, NY 10022 USA
来源：
MATHEMATICAL PROGRAMMING | 2007年 / 109卷 / 2-3期
关键词：
semidefinite programming; eigenvalue optimization; subgradient bundle methods; Lanczos method; parallel computing;
D O I：
10.1007/s10107-006-0032-1
中图分类号：
TP31 [计算机软件];
学科分类号：
081202 ; 0835 ;
摘要：
We describe an approach to the parallel and distributed solution of large-scale, block structured semidefinite programs using the spectral bundle method. Various elements of this approach (such as data distribution, an implicitly restarted Lanczos method tailored to handle block diagonal structure, a mixed polyhedral-semidefinite subdifferential model, and other aspects related to parallelism) are combined in an implementation called LAMBDA, which delivers faster solution times than previously possible, and acceptable parallel scalability on sufficiently large problems.
引用
收藏
页码：477 / 504
页数：28
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