Soft digital signal processing

  • Authors:
  • Rajamohana Hegde;Naresh R. Shanbhag

  • Affiliations:
  • Univ. of Illinois, Urbana;Univ. of Illinois, Urbana

  • Venue:
  • IEEE Transactions on Very Large Scale Integration (VLSI) Systems - System Level Design
  • Year:
  • 2001

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Abstract

In this paper, we propose a framework for low-energy digital signalprocessing (DSP), where the supply voltage is scaled beyond thecritical voltage imposed by the requirement to match the criticalpath delay to the throughput. This deliberate introduction ofinput-dependent errors leads to degradation in the algorithmicperformance, which is compensated for via algorithmicnoise-tolerance (ANT) schemes. The resulting setup thatcomprises of the DSP architecture operating at subcritical voltageand the error control scheme is referred to as soft DSP. Theeffectiveness of the proposed scheme is enhanced when arithmeticunits with a higher "delay imbalance" are employed. Aprediction-based error-control scheme is proposed to enhance theperformance of the filtering algorithm in the resence of errors dueto soft computations. For a frequency selective filter, it is shownthat the proposed scheme provides 60-81% reduction in energydissipation for filter bandwidths up to 0.5π (where 2πcorresponds to the sampling frequency fs) overthat achieved via conventional architecture and voltage scaling,with a maximum of 0.5-dB degradation in the output signal-to-noiseratio (SNRO). It is also shown that the proposedalgorithmic noise-tolerance schemes can also be used to improve theperformance of DSP algorithms in presence of bit-error rates of upto 10−3 due to deep submicron (DSM) noise.