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Energy-efficient Mapping of Task Collections onto Manycore Processors

Streaming applications consist of a number of tasks that all run concurrently, and that process data at certain rates. On manycore processors, the tasks of the streaming application must be mapped onto the cores. While load balancing of such applications has been considered, especially in the MPSoC community, we investigate energy-efficient mapping of such task collections onto manycore processors. We first derive rules that guide the mapping process and show that as long as dynamic power consumption dominates static power consumption, the latter can be ignored and the problem reduces to load balancing. When however, as expected in the coming years, static power consumption will be a notable fraction of total power consumption, then an energy-efficient mapping must take it into account, e.g. by temporary shutdown of cores or by restricting the number of cores. We validate our findings with synthetic and real-world applications on the Intel SCC manycore processor.