Energy Reduction by Workload Adaptation in a Multi-Process Environment

Reducing energy consumption is an important issue in modern computers. Dynamic power management (DPM) has been extensively studied in recent years. One approach for DPM is to adjust workloads, such as clustering or eliminating requests, as a way to trade-off energy consumption and quality of services. Previous studies focus on single processes. However, when multiple concurrently running processes are considered, workload adjustment must be determined based on the interleaving of the processes' requests. When multiple processes share the same hardware component, adjusting one process may not save energy. This paper presents an approach to assign energy responsibility to individual processes based on how they affect power management. The assignment is used to estimate potential energy reduction by adjusting the processes. We use the estimation to guide runtime adaptation of workload behavior. Experiments demonstrate that our approach can save more energy and improve energy efficiency.