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Low Power Design Using RNS

Power dissipation has become one of the major limiting factors in the design of digital ASICs. Low power dissipation will increase the mobility of the ASIC by reducing the system cost, size and weight. DSP blocks are a major source of power dissipation in modern ASICs. The residue number system (RNS) has, for a long time, been proposed as an alternative to the regular two's complement number system (TCS) in DSP applications to reduce the power dissipation. The basic concept of RNS is to first encode the input data into several smaller independent residues. The computational operations are then performed in parallel and the results are eventually decoded back to the original number system. Due to the inherent parallelism of the residue arithmetics, hardware implementation results in multiple smaller design units. Therefore an RNS design requires low leakage power cells and will result in a lower switching activity. The residue number system has been analyzed by first investigating different implementations of RNS adders and multipliers (which are the basic arithmetic functions in a DSP system) and then deriving an optimal combination of these. The optimum combinations have been used to implement an FIR filter in RNS that has been compared with a TCS FIR filter. By providing different input data and coefficients to both the RNS and TCS FIR filter an evaluation of their respective performance in terms of area, power and operating frequency have been performed. The result is promising for uniform distributed random input data with approximately 15 % reduction of average power with RNS compared to TCS. For a realistic DSP application with normally distributed input data, the power reduction is negligible for practical purposes.

Identiferoai:union.ndltd.org:UPSALLA1/oai:DiVA.org:liu-110176
Date January 2014
CreatorsClasson, Viktor
PublisherLinköpings universitet, Elektroniksystem, Linköpings universitet, Tekniska högskolan
Source SetsDiVA Archive at Upsalla University
LanguageEnglish
Detected LanguageEnglish
TypeStudent thesis, info:eu-repo/semantics/bachelorThesis, text
Formatapplication/pdf
Rightsinfo:eu-repo/semantics/openAccess

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