DocumentCode
3088648
Title
Reconfigurable Parallel Processing System Based on A Modified Ant Colony Algorithm
Author
Saad, E.M. ; El Adawy, M. ; Keshk, H.A. ; Habashy, Shahira M.
Author_Institution
Helwan Univ., Cairo
Volume
0
fYear
2006
fDate
14-16 March 2006
Firstpage
1
Lastpage
11
Abstract
Ant colony optimization is an evolutionary approach where a number of ants search for good solutions. Ant Algorithms often show good optimization results. This paper, discusses number of algorithms built using modified ant colony algorithm which are used to solve the problem of assigning each task in a given task graph to a processor in a reconfigurable multi processor architecture so as to minimize the total overall execution time of the tasks. Each group of ants is working collectively to find the interconnection architecture best suited for the task graph and the best scheduling of that task graph on the chosen interconnection architecture. The total execution time is computed according to the knowledge of individual run times of tasks and the communication requirements among tasks. The inter task communication time is dependent on the interconnection processor architecture. The results of using modified ant colony algorithm in reconfigurable parallel processor system are compared with that of using genetic algorithm for solving the same problem
Keywords
genetic algorithms; graph theory; multiprocessor interconnection networks; parallel architectures; reconfigurable architectures; genetic algorithm; interconnection architecture; modified ant colony optimization; multiprocessor architecture; reconfigurable parallel processing system; task graph; Algorithm design and analysis; Ant colony optimization; Circuit topology; Computer architecture; Genetic algorithms; Network topology; Parallel algorithms; Parallel processing; Processor scheduling; Routing;
fLanguage
English
Publisher
ieee
Conference_Titel
Radio Science Conference, 2006. NRSC 2006. Proceedings of the Twenty Third National
Conference_Location
Menoufiya
Print_ISBN
977-5031-84-2
Electronic_ISBN
977-5031-84-2
Type
conf
DOI
10.1109/NRSC.2006.386362
Filename
4275159
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