CPU MISER: A Performance-Directed Run-Time System for Power Aware Cluster

Performance and power are two primary design constraints in today’s high-end computing systems. Because of the inherent dependency between performance and power, reducing power consumption without impacting system performance is a challenge for the HPC community. In this paper, we present a run-time system as well as its underlying performance model for performance-directed, power-aware cluster computing. Experimental results based on physical measurements show that NPB benchmarks benefit up to 36% energy saving and 21% performance gain. On average, our run-time system leads to 10.7% energy saving with 1.2% performance loss over 9 NPB benchmarks, and is 1.59X improvement in ED2P than CPUSPEED. We also show that our system is performance directed in the sense that the performance loss for most application is within the user specified limit. We attribute the promising results to the accurate performance modeling and prediction, and effective performance control techniques