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DESIGN SPACE EXPLORATION: COMPARAITIVE STUDY OF SIMULATED ANNEALING AND PARTICLE SWARM OPTIMIZATION

As the complexity of designs implemented in embedded system increases, there needs to be some sort of exploration of hardware configurations to find the best design that will meet the design constraints. Design Space Exploration is an exploration technique should by many to find the best hardware configuration to fit in some design constraints. In this project, a popular algorithm, Simulated Annealing and a relatively new algorithm, Particle Swarm Optimization are analyzed and implemented to perform space exploration on a Fuzzy Logic Coprocessor. Results from both algorithms are observed and compared to suggest a more efficient algorithm. The Fuzzy Logic Coprocessor is a small design with very low complexity. This makes the analysis of Simulated Annealing and Particle Swarm Optimization much easier to understand and then with a strong foundation, the problem complexity can increase and more results can be gathered from the algorithms.