Novel Heuristic Mapping Algorithms for Design Space Exploration of Multiprocessor Embedded Architectures

Abstract

Electronic System level design has an important role in the multi-processor embedded system on chip design. Two important steps in this process are evaluation of a single design configuration and design space exploration. In the first part of design process, high-level simple analytical models for application mapping and evaluation are used and modified aiming at accelerating the evaluation of a single design configuration. Using the analytical model the design space is pruned and explored at high speed with low accuracy. In the second part of the design process, two Multi Objective Optimization Algorithms based on Particle Swarm Optimization and Simulated Annealing have been proposed to perform design space exploration of the pruned design space with higher accuracy taking advantages of low-level architectural simulation engines. The results obtained by proposed algorithms will provide the designer more accurate solutions within an acceptable time. Considering the MJPEG application as the case study, each of these methods produces a set of near-optimal points. Simulation results show that the proposed methods can lead to near-optimal design configurations with acceptable accuracy in reasonable time.