DocumentCode :
2604045
Title :
Comparative study of COW and SMP computer configurations
Author :
Godza, Gavril ; Cristea, Valentin
Author_Institution :
Comput. Sci. Dept., Univ. Politehnica of Bucharest, Romania
fYear :
2002
fDate :
2002
Firstpage :
205
Lastpage :
210
Abstract :
The class of MIMD parallel computers includes multiprocessor architectures, such as UMA, COMA, and NUMA, as well as multicomputer architectures, such as MPP and COW. Despite huge technological differences, machines with different architectures may be used to run certain similar applications. An interesting category of applications that may be successfully executed on a variety of parallel architectures is that of genetic algorithms (GAs) that provide more and more attractive solution of many complex engineering problems for which classical optimization methods cannot be used. GAs prove to be parallelizable in a natural way. Parallel genetic algorithms (PGAs) highlight good balance between calculations and communications that allows obtaining good results on different classes of parallel architectures. The paper describes the results obtained in a comparative study of PGAs, implemented on a cluster of SunBlade 100 workstations (COW) and on a Sun Enterprise E10000 (UMA) computer. The study demonstrates suitability of these different architectures for the development and execution of this class of applications. Also, some relevant facts concerning the performance of PGAs are presented.
Keywords :
genetic algorithms; message passing; parallel algorithms; parallel architectures; parallel machines; performance evaluation; shared memory systems; workstation clusters; COW computer configuration; MIMD; SMP computer configuration; Sun Enterprise E10000; SunBlade 100; distributed algorithms; evolutionary computing; message passing; multicomputer architectures; multiprocessor architectures; optimization; parallel architectures; parallel computers; parallel genetic algorithms; performance; workstation cluster; Application software; Computer architecture; Concurrent computing; Electronics packaging; Genetic algorithms; Genetic engineering; Optimization methods; Parallel architectures; Sun; Workstations;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Parallel Computing in Electrical Engineering, 2002. PARELEC '02. Proceedings. International Conference on
Print_ISBN :
0-7695-1730-7
Type :
conf
DOI :
10.1109/PCEE.2002.1115241
Filename :
1115241
Link To Document :
بازگشت