Uncertain< T >: Abstractions for Uncertain Hardware and Software

  • James Bornholt ,
  • Todd Mytkowicz ,
  • Kathryn S McKinley

IEEE MICRO Top Picks | , Vol 35(3): pp. 132-143

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Building correct, efficient systems that reason about the approximations produced by sensors, machine learning, big data, humans, and approximate hardware and software requires new standards and abstractions. The Uncertain software abstraction aims to tackle these pervasive correctness, optimization, and programmability problems and guide hardware and software designers in producing estimates.

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