DocumentCode
2681240
Title
Hardware Software Partitioning Problem in Embedded System Design Using Particle Swarm Optimization Algorithm
Author
Bhattacharya, Alakananda ; Konar, Amit ; Das, Swagatam ; Grosan, Crina ; Abraham, Ajith
Author_Institution
Dept. of Electron. & Telecommun. Eng., Jadavpur Univ., Kolkata
fYear
2008
fDate
4-7 March 2008
Firstpage
171
Lastpage
176
Abstract
Hardware/software partitioning is a crucial problem in embedded system design. In this paper, we provide an alternative approach to solve this problem using particle swarm optimization (PSO) algorithm. Performance analysis of the proposed scheme with integer linear programming, genetic algorithm and ant colony optimization technique has been compared using standard benchmark datasets, and the computer simulations reveal that the proposed approach outperforms all the meta-heuristic based existing techniques with respect to cumulative runtimes for several runs of the same program. The integer linear programming has been found to yield the optimal solutions, and the proposed swarm scheme yields sub-optimal solution, sufficiently close to the reported results obtained for integer programming.
Keywords
embedded systems; hardware-software codesign; integer programming; linear programming; particle swarm optimisation; ant colony optimization; computer simulations; embedded system design; genetic algorithm; hardware software partitioning problem; integer linear programming; meta-heuristic techniques; particle swarm optimization algorithm; performance analysis; Algorithm design and analysis; Embedded software; Embedded system; Genetic algorithms; Hardware; Integer linear programming; Particle swarm optimization; Partitioning algorithms; Performance analysis; Software algorithms; Genetic Algorithm; Hardware/Software Partitioning; Integer Linear Programming; Particle Swarm Optimization;
fLanguage
English
Publisher
ieee
Conference_Titel
Complex, Intelligent and Software Intensive Systems, 2008. CISIS 2008. International Conference on
Conference_Location
Barcelona
Print_ISBN
978-0-7695-3109-0
Type
conf
DOI
10.1109/CISIS.2008.5
Filename
4606678
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