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High performance grid and cluster computing for some optimization problems

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4 Author(s)
K. Fujisawa ; Dept. of Math. Sci., Tokyo Denki Univ., Japan ; M. Kojima ; A. Takeda ; M. Yamashita

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 with numerical results are reported.

Published in:

Applications and the Internet Workshops, 2004. SAINT 2004 Workshops. 2004 International Symposium on

Date of Conference:

26-30 Jan. 2004