Online Strategies for High-performance Power-aware Thread Execution on Emerging Multiprocessors

Granularity control is an effective means for trading power consumption with performance on dense shared mem-ory multiprocessors, such as multi-SMT and multi-CMP sys-tems. With granularity control, the number of threads used to execute an application, or part of an application, is changed, thereby also changing the amount of work done by each ac-tive thread. In this paper, we analyze the energy/performance trade-off of varying thread granularity in parallel bench-marks written for shared memory systems. We use physical experimentation on a real multi-SMT system and a power es-timation model based on the die areas of processor compo-nents and component activity factors obtained from a hard-ware event monitor. We also present HPPATCH, a runtime al-gorithm for live tuning of thread granularity, which attempts to simultaneously reduce both execution time and processor power consumption.