Profile-based Optimization of Power Performance by using Dynamic Voltage Scaling on a PC cluster

Currently, several of the high performance processors used in a PC cluster have a DVS (Dynamic Voltage Scal-ing) architecture that can dynamically scale processor volt-age and frequency. Adaptive scheduling of the voltage and frequency enables us to reduce power dissipation without a performance slowdown during communication and mem-ory access. In this paper, we propose a method of profiled-based power-performance optimization by DVS scheduling in a high-performance PC cluster. We divide the program execution into several regions and select the best gear for power efficiency. Selecting the best gear is not straight-forward since the overhead of DVS transition is not free. We propose an optimization algorithm to select a gear us-ing the execution and power profile by taking the transi-tion overhead into account. We have built and designed a power-profiling system, PowerWatch. With this system we examined the effectiveness of our optimization algorithm on two types of power-scalable clusters (Crusoe and Turion). According to the results of benchmark tests, we achieved almost 40 % reduction in terms of EDP (energy-delay prod-uct) without performance impact (less than 5%) compared to results using the standard clock frequency.