MAR: A Novel Power Management for CMP Systems in Data-Intensive Environment

Abstract

Emerging data-intensive applications are creating non-uniform CPU and I/O workloads which impose the requirement to consider both CPU and I/O effects in the power management strategies. Current approaches focus on scaling down the CPU frequency based on CPU busy/idle ratio without taking I/O into considertation. Therefore, they do not fully exploit the opportunities in power conservation. In this paper, we propose a novel power management scheme called model-free, adaptive, rule-based (MAR) in multiprocessor systems to minimize the CPU power consumption subject to performance constraints. By introducing new I/O wait status, MAR is able to accurately describe the relationship between core frequencies, performance and power consumption. Moreover, we adopt a model-free control method to filter out the I/O wait status from the traditional CPU busy/idle model in order to achieve fast responsiveness to burst situations and take full advantage of power saving. Our extensive experiments on a physical testbed demonstrate that, for SPEC benchmarks and data-intensive (TPC-C) benchmarks, an MAR prototype system achieves 95.8-97.8 percent accuracy of the ideal power saving strategy calculated offline. Compared with baseline solutions, MAR is able to save 12.3-16.1 percent more power while maintain a comparable performance loss of about 0.78-1.08 percent. In addition, more simulation results indicate that our design achieved 3.35-14.2 percent more power saving efficiency and 4.2-10.7 percent less performance loss under various CMP configurations as compared with various baseline approaches such as LAST, Relax, PID and MPC.