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 memory multiprocessors, such as multi-SMT and multi-CMP systems. In this paper, we analyze the energy/performance trade-off of varying thread granularity in parallel benchmarks written for shared memory systems. We use physical experimentation on a real multi-SMT system and a power estimation model based on the die areas of processor components and component activity factors obtained from a hardware event monitor. We also present HPPATCH, a runtime algorithm for live tuning of thread granularity, which attempts to simultaneously reduce execution time and processor power consumption.

• Type: Conference
• Year: 2006
• Where: IPPS
• Authors: Matthew Curtis-Maury, James Dzierwa, Christos D. Antonopoulos, Dimitrios S. Nikolopoulos
• Keywords: Distributed And Parallel Computing, IPPS 2006, Power Consumption, Shared Memory, Thread Granularity