Energy Optimization for Scientific Programs Using Auto-tuning Language ppOpen-AT
Takahiro Katagiri, Cheng Luo, Reiji Suda, Shoichi Hirasawa, Satoshi Ohshima · 2013
In this paper, we demonstrate a new approach for power-consumption optimization using a dedicated Auto-tuning (AT) language. Our approach is based on recently developed technologies: (1) a power measurement application programming interface, (2) an AT mathematical core library. Preliminary performance evaluation enables us to select the best kernel for a real-world scientific program using either the CPU or Graphics Processing Unit, with respect to energy consumption. From the results of the evaluation, we found the performance-changing point in the experimental environment.