Evaluation of partitioning methods for stream applications on a heterogeneous multi-core processor simulator

In this paper, we explore coordination of multiple cores in a single processor to achieve better performance and lower real time power consumption for single multimedia streaming application, as opposed to multiple independent applications executing in a parallel fashion. Two strategies of application partitioning, i.e. partitioning by data or function, are evaluated by implementing an audio application, which is to encode audio signals in G.721 protocol, on two partitions. To execute these partitioned tasks, we improve a multi-core processor simulator, whose performance, power metrics were verified before, by enabling real time power consumption. The coordination of multiple cores is assured with explicit inter-core communication which is also enabled in the simulator. It is interesting to find that partitioning by function outperforms partitioning by data in terms of both performance and power consumption. The observation, which should be valid for most of streaming applications, would be a good reference for system architects. The implementation in the paper also underscores the importance of and the need for coordinating multiple cores on a single processor via inter-core communications.