Cost-performance tradeoffs in unreliable computation architectures

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We investigate unreliable computation problem under cost and fidelity constraints. We introduce a framework, where we observe a noise-corrupted version of correct computation while incurring an associated cost. We consider several cost models formalizing the relationship between fidelity of an unreliable computation and its cost. We demonstrate that a single unreliable computation incurs less cost than a fusion of several less costly and less reliable computations while achieving same MSE performance under concave and linear costs. We show that fusing several less costly and less reliable computation yield a better cost-performance tradeoff than a single unreliable computation under convex costs.

Original languageEnglish (US)
Title of host publicationConference Record of the 50th Asilomar Conference on Signals, Systems and Computers, ACSSC 2016
EditorsMichael B. Matthews
PublisherIEEE Computer Society
Pages215-219
Number of pages5
ISBN (Electronic)9781538639542
DOIs
StatePublished - Mar 1 2017
Event50th Asilomar Conference on Signals, Systems and Computers, ACSSC 2016 - Pacific Grove, United States
Duration: Nov 6 2016Nov 9 2016

Publication series

NameConference Record - Asilomar Conference on Signals, Systems and Computers
ISSN (Print)1058-6393

Other

Other50th Asilomar Conference on Signals, Systems and Computers, ACSSC 2016
CountryUnited States
CityPacific Grove
Period11/6/1611/9/16

ASJC Scopus subject areas

  • Signal Processing
  • Computer Networks and Communications

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  • Cite this

    Donmez, M. A., Raginsky, M., Singer, A. C., & Varshney, L. R. (2017). Cost-performance tradeoffs in unreliable computation architectures. In M. B. Matthews (Ed.), Conference Record of the 50th Asilomar Conference on Signals, Systems and Computers, ACSSC 2016 (pp. 215-219). [7869027] (Conference Record - Asilomar Conference on Signals, Systems and Computers). IEEE Computer Society. https://doi.org/10.1109/ACSSC.2016.7869027