Software implementation strategies for power-conscious systems

Abstract

A variety of systems with possibly embedded computing power, such as small portable robots, hand-held computers, and automated vehicles, have power supply constraints. Their batteries generally last only for a few hours before being replaced or recharged. It is important that all design efforts are made to conserve power in those systems. Energy consumption in a system can be reduced using a number of techniques, such as low-power electronics, architecture-level power reduction, compiler techniques, to name just a few. However, energy conservation at the application software-level has not yet been explored. In this paper, we show the impact of various software implementation techniques on energy saving. Based on the observation that different instructions of a processor cost different amount of energy, we propose three energy saving strategies, namely (i) assigning live variables to registers, (ii) avoiding repetitive address computations, and (iii) minimizing memory accesses. We also study how a variety of algorithm design and implementation techniques affect energy consumption. In particular, we focus on the following aspects: (i) recursive versus iterative (with stacks and without stacks), (ii) different representations of the same algorithm, (iii) different algorithms - with identical asymptotic complexity - for the same problem, and (iv) different input representations. We demonstrate the energy saving capabilities of these approaches by studying a variety of applications related to power-conscious systems, such as sorting, pattern matching, matrix operations, depth-first search, and dynamic programming. From our experimental results, we conclude that by suitably choosing an algorithm for a problem and applying the energy saving techniques, energy savings in excess of 60% can be achieved.