Association for Computing Machinery
In this paper, the authors present an efficient technique to perform design space exploration of a multi-processor platform that minimizes the number of simulations needed to identify the power-performance approximate Pareto curve. Instead of using semi-random search algorithms (like simulated annealing, tabu search, genetic algorithms, etc.), they use domain knowledge derived from the platform architecture to setup exploration as a decision problem. Each action in the decision-theoretic framework corresponds to a change in the platform parameters.