Abstract

We investigate fusing several unreliable computational units that perform the same task. We model an unreliable computational outcome as an additive perturbation to its error-free result in terms of its fidelity and cost. We analyze reliability of replication-based strategies that distribute cost across several unreliable units and fuse their outcomes. When the cost is a convex function of fidelity, the optimal replication-based strategy in terms of incurred cost while achieving a target mean-square error level may fuse several unreliable computational units. For concave and linear costs, a single more reliable unit incurs lower cost compared to fusion of several lower cost and less reliable units while achieving the same mean-square error level. We show how our results give insight into problems from theoretical neuroscience and circuits.

Original languageEnglish (US)
Article number9099434
Pages (from-to)77-89
Number of pages13
JournalIEEE Open Journal of Signal Processing
Volume1
DOIs
StatePublished - 2020

Keywords

  • Cost-reliability tradeoff
  • Fidelity
  • Fusion
  • In-sensor computing
  • Redundancy
  • Unreliable computation

ASJC Scopus subject areas

  • Signal Processing

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