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IEEE TRANSACTIONS ON VERY LARGE SCALE INTEGRATION (VLSI) SYSTEMS, VOL. 10, NO. 2, APRIL 2002 135 Energy Scalable System Design Amit Sinha, Alice Wang, and Anantha Chandrakasan Abstract— We introduce the notion of energy-scalable system- design. The principal idea is to maximize computational quality for a given energy constraint at all levels of the system hierarchy. The desirable energy-quality (E–Q) characteristics of systems are dis- cussed. E–Q behavior of algorithms is considered and transforms that significantly improve scalability are analyzed using three dis- tinct categories of commonly used signal-processing algorithms on the StrongARM SA-1100 processor as examples ( viz. , filtering, fre- quency domain transforms and classification). Scalability hooks in hardware are analyzed using similar examples on the Pentium III processor and a scalable programming methodology is pro- posed. Design techniques for true energy scalable hardware are also demonstrated using filtering as an example. Index Terms— Algorithmic transforms, energy scalable, low power, variable precision. I. INTRODUCTION I N EMBEDDED systems, energy is a precious resource and must be used efficiently. Therefore, it is highly desirable that we structure our algorithms and systems in such a fashion that computational accuracy can be traded off with energy re- quirement. At the heart of such transformations lies the con- cept of incremental refinement [1]. Consider a scenario where an individual is using his laptop for a video telephone applica- tion. Based on the current battery state and overall power-con- sumption model [2] the system should be able to predict its up- time. If the battery life is insufficient, the user might choose to tradeoff some quality/performance and extend the battery life of his laptop. Consider another scenario where a distributed sensor network [3] is being used to monitor seismic activity from a re- mote basestation. Sensor nodes are energy constrained and have a finite lifetime. It would be highly desirable to have energy scal- able algorithms and protocols running on the sensor network. The remote basestation should have the capability to dynami- cally reduce energy consumption (to prolong mission lifetime if uninteresting events have occurred) by altering the throughput and computation accuracy. This type of behavior necessitates system redesign so that every computational step leads us in- crementally closer to the output. Manuscript received December 9, 2000; revised March 13, 2002. This work was supported in part by the Defense Advanced Research Projects Agency (DARPA) and in part by the Air Force Research Laboratory, Air Force Material Command, USAF, under Agreement F30602-00-2-0551. A. Sinha was with the Electrical Engineering and Computer Science De-
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This note was uploaded on 09/01/2009 for the course CSE CS-699 taught by Professor Prf.p.bhaduri during the Spring '09 term at Indian Institute of Technology, Guwahati.

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