Paper Info
Title
High Performance Grid and Cluster Computing for Some Optimization Problems
Abstract
The aim of this short article is to show that grid and cluster computing provides tremendous power to optimization methods. The methods that the article picks up are a successive convex relaxation method for quadratic optimization problems, a polyhedral homotopy method for polynomial systems of equations and a primal-dual interior-point method for semidefinite programming problems. Their parallel implementations on grids and clusters together withnumerical results are reported.
Year
DOI
Venue
2004
10.1109/SAINTW.2004.1268696
SAINT Workshops
Keywords
Field
DocType
cluster computing,parallel implementation,tremendous power,polynomial system,primal-dual interior-point method,successive convex relaxation method,semidefinite programming problem,quadratic optimization problem,polyhedral homotopy method,high performance grid,optimization problems,short article,optimization problem,quadratic optimization,grid computing
Mathematical optimization,Grid computing,Quadratically constrained quadratic program,Polynomial,Computer science,Quadratic programming,Optimization problem,Grid,Semidefinite programming,Computer cluster
Conference
ISBN
Citations 
PageRank 
0-7695-2050-2
0
0.34
References 
Authors
7
4
Name
Order
Citations
PageRank
Katsuki Fujisawa124828.63
Masakazu Kojima21603222.51
Akiko Takeda319629.72
Makoto Yamashita413613.74