A statistical approach for parallel optimization with application to VLSI placement

Author

Efe, Kemal

Author_Institution

Center for Adv. Comput. Studies, Southwestern Louisiana Univ., Lafayette, LA, USA

fYear

1991

fDate

20-24 May 1991

Firstpage

518

Lastpage

525

Abstract

A massively parallel optimization approach based on simple neighborhood search techniques was developed and applied to the problem of VLSI cell placement. Statistical models are developed to analyze the performance of the approach in general, and to derive statistical bounds on the quality of obtainable results. The results of these analyses suggest a simple framework for approximate solution of difficult problems. The approach is inherently parallel, and it can be implemented on any type of parallel computer. It was implemented on a simulated hypercube MIMD machine using Cosmic C on a network of Sun workstations. The method is empirically verified

Keywords

VLSI; circuit layout CAD; optimisation; search problems; Cosmic C; Sun workstations; VLSI placement; neighborhood search techniques; parallel optimization; simulated hypercube MIMD machine; statistical approach; statistical bounds; Application software; Computational modeling; Concurrent computing; Costs; Hypercubes; Search methods; Simulated annealing; Sun; Testing; Very large scale integration;

fLanguage

English

Publisher

ieee

Conference_Titel

Distributed Computing Systems, 1991., 11th International Conference on

Conference_Location

Arlington, TX

Print_ISBN

0-8186-2144-3

Type

conf

DOI

10.1109/ICDCS.1991.148720

Filename

148720