Workload-based power management for parallel computer systems

This paper describes and evaluates predictive power management algorithms that we have developed to minimize energy consumption and unmet demand in parallel computer systems. The algorithms are evaluated using workload data obtained from production servers from several applications, showing that energy savings of 20% or more can readily be achieved, with a small degree of unmet demand and acceptable reliability, availability, and serviceability (RAS) impact. The implementation of these algorithms in IBM system management software and the possibilities for future work are discussed.