chmw03 - Modeling the Power Consumption of Audio Signal...

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Modeling the Power Consumption of Audio Signal Processing Computations Using Customized Numerical Representations Roger Chamberlain, Eric Hemmeter, Robert Morley, Jason White Roger Chamberlain, Eric Hemmeter, Robert Morley, and Jason White, “Modeling the Power Consumption of Audio Signal Processing Computations Using Customized Numerical Representations,” in Proc. of the 36th Annual Simulation Symposium , April 2003, pp. 249-255. School of Engineering and Applied Science Washington University Campus Box 1115 One Brookings Dr. St. Louis, MO 63130-4899
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Modeling the Power Consumption of Audio Signal Processing Computations Using Customized Numerical Representations Roger Chamberlain*†, Eric Hemmeter*, Robert Morley*, and Jason White* *School of Engineering and Applied Science, Washington University, St. Louis, Missouri Hearing Emulations, LLC, and BECS Technology, Inc., St. Louis, Missouri [email protected], [email protected], [email protected], [email protected] Abstract This paper explores the impact that numerical representation has on the power consumption of audio signal processing applications. The motivation is digital hearing aids, for which minimizing the power consumption is a critical design goal. We investigate two aspects of this problem. First, we evaluate the validity of using signal transition counts to model actual power consumption within this problem domain, and second, we compare the relative power consumption of multiply- accumulate operations for several customized numerical representations. Keywords: audio signal processing, power consumption, numerical representation 1. Introduction One of the major technical issues facing the designers of modern, hand-held, portable, digital systems is the need to minimize the power consumption of the system to prolong battery life. Many of these systems perform signal processing functions on audio signals (e.g., hearing aids, communications systems, MP3 players, etc). As new signal processing techniques are proposed, the computational requirements invariably grow, putting additional pressure on power consumption. In this work, we are investigating the use of non-standard numerical representations for processing audio signals, showing how the power consumption can be lowered for audio signal processing while maintaining (and even improving) overall signal quality. Standard numerical representations used for signal processing applications include fixed-point representations (typically 16 bits) and floating-point representations (either 32- or 64-bit IEEE standard). The choices of representation available to system designers are based largely upon historical convention rather than the specific needs of the application. Our purpose is to investigate the implications of deviating from these standard representations and designing a system with a numerical representation tailored to the specific application. Our specific motivating application is the design of
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chmw03 - Modeling the Power Consumption of Audio Signal...

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