Quantifying the impact of frequency scaling on the energy efficiency of the single-chip cloud computer

Dynamic frequency and voltage scaling (DVFS) techniques have been widely used for meeting energy constraints. Single-chip many-core systems bring new challenges owing to the large number of operating points and the shift to message passing interface (MPI) from shared memory communication. DVFS, however, has been mostly studied on single-chip systems with one or few cores, without considering the impact of the communication among cores. This paper evaluates the impact of frequency scaling on the performance and power of many-core systems with MPI. We conduct experiments on the Single-Chip Cloud Computer (SCC), an experimental many-core processor developed by Intel. The paper first introduces the run-time monitoring infrastructure and the application suite we have designed for an in-depth evaluation of the SCC. We provide an extensive analysis quantifying the effects of frequency perturbations on performance and energy efficiency. Experimental results show that runtime communication patterns lead to significant differences in power/performance tradeoffs in many-core systems with MPI