Solving large-scale semidefinite programs in parallel

作     者：Nayakkankuppam, Madhu V. 

作者机构：Bloomberg LP Computat Finance Grp New York NY 10022 USA 

出 版 物：《MATHEMATICAL PROGRAMMING》 (数学规划)

年 卷 期：2007年第109卷第2-3期

页      面：477-504页

核心收录：

学科分类：1201[管理学-管理科学与工程(可授管理学、工学学位)] 07[理学] 070104[理学-应用数学] 0835[工学-软件工程] 0701[理学-数学] 

主　　题：semidefinite programming eigenvalue optimization subgradient bundle methods Lanczos method parallel computing 

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.