Algorithmic transforms for efficient energy scalable computation

Authors:
Amit Sinha;Alice Wang;Anantha P. Chandrakasan
Affiliations:
Department of EECS, Massachusetts Institute of Technology, Cambridge, MA;Department of EECS, Massachusetts Institute of Technology, Cambridge, MA;Department of EECS, Massachusetts Institute of Technology, Cambridge, MA
Venue:
ISLPED '00 Proceedings of the 2000 international symposium on Low power electronics and design
Year:
2000

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Abstract

We introduce the notion of energy scalable computation on general purpose processors. The principle idea is to maximize computational qualityfor a given energy constraint. Teh desirable energy-quality behavior of algorithms is discussed. subsequently the energy-quality scalability of three distinct categories of commonly used signal processing algorithms (viz. filtering, frequency domain transforms and classification) are analyzed on the StrongARM SA-1100 processor and transformations are described which obtain significant improvements in the energy-quality scalability of the algorithm.