Analyzing and optimizing energy efficiency of algorithms on DVS systems a first step towards algorithmic energy minimization

Authors:
Tetsuo Yokoyama;Gang Zeng;Hiroyuki Tomiyama;Hiroaki Takada
Affiliations:
Nagoya University, Nagoya, Aichi;Nagoya University, Nagoya, Aichi;Nagoya University, Nagoya, Aichi;Nagoya University, Nagoya, Aichi
Venue:
Proceedings of the 2009 Asia and South Pacific Design Automation Conference
Year:
2009

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Abstract

The energy efficiency at the algorithmic level on DVS systems and its analysis and optimization methods are presented. Given a problem the most energy efficient algorithm is not uniquely determined but dependent on multiple factors, including intratask dynamic voltage scaling (IntraDVS) policies, the size of intermediate data structure, and the size of inputs. We show that at the algorithmic level principles behind energy optimization and performance optimization are not identical. We propose a metric for evaluating optimal energy efficiency of static voltage scaling (SVS) and a few new effective IntraDVS policies employing data flow information. Experimental results on sorting algorithms show the existence of several tradeoffs in terms of energy consumption. Transforming algorithms by employing problem specific knowledge and data flow information successfully improves their energy efficiency.