Latency-aware DVFS for Efficient Power State Transitions on Many-core Architectures

Abstract

Energy efficiency is quickly becoming a first-class design constraint in high-performance computing (HPC). We need more efficient power management solutions to save energy costs and carbon footprint of HPC systems. Dynamic voltage and frequency scaling (DVFS) is a commonly used power management technique for making a trade-off between power consumption and system performance according to the time-varying program behavior. However, prior work on DVFS seldom takes into account the voltage and frequency scaling latencies, which we found to be a crucial factor determining the efficiency of the power management scheme. Frequent power state transitions without latency awareness can make a real impact on the execution performance of applications. The design of multiple voltage domains in some many-core architectures has made the effect of DVFS latencies even more significant. These concerns lead us to propose a new latency-aware DVFS scheme to adjust the optimal power state more accurately. Our main idea is to analyze the latency characteristics in depth and design a novel profile-guided DVFS solution which exploits the varying execution patterns of the parallel program to avoid excessive power state transitions. We implement the solution into a power management library for use by shared-memory parallel applications. Experimental evaluation on the Intel SCC many-core platform shows significant improvement in power efficiency after using our scheme. Compared with a latency-unaware approach, we achieve 24.0 % extra energy saving, 31.3 % more reduction in the energy---delay product and 15.2 % less overhead in execution time in the average case for various benchmarks. Our algorithm is also proved to outperform a prior DVFS approach attempted to mitigate the latency effects.