Algorithmic transforms for efficient energy scalable computation

We introduce the notion of energy scalable computation on general purpose processors. The principle idea is to maximize computational quality for a given energy constraint. The 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.