Energy-aware partitioning for on-chip bus architecture using a multi-objective genetic algorithm

Incorporating power management during partitioning at the system level contributes considerably to energy efficient architecture. Designers commonly implement systems as a mix of partitioning blocks of various sizes, connected using bus interconnection architecture. Therefore, the use of a partitioning approach that partitions a system with the greatest possible idle time on a dedicated interconnection architecture has become unpractical for power management development. This work presents a novel energy-aware hardware clustering algorithm with a performance estimator for on-chip bus based architectures during high level synthesis, to enhance the quality of solutions for implementing power management systems. Experimental results obtained in four cases reveal that the proposed strategy generates a wide range of cost-effective solutions and is highly effective for today's hardware systems.