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15 - Programming Unreliable Hardware

Published online by Cambridge University Press:  18 November 2020

By
Michael Carbin  and
Sasa Misailovic
Edited by
Gilles Barthe ,
Joost-Pieter Katoen  and
Alexandra Silva
Gilles Barthe
Affiliation:
Max Planck Institute for Security and Privacy
Joost-Pieter Katoen
Affiliation:
RWTH Aachen University, Germany
Alexandra Silva
Affiliation:
University College London
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Summary

Emerging high-performance architectures are anticipated to contain unreliable components that may exhibit soft errors, which silently corrupt the results of computations. Full detection and masking of soft errors is challenging, expensive and, for some applications, unnecessary. For example, approximate computing applications (such as multimedia processing, machine learning and big data analytics) can often naturally tolerate soft errors.In this chapter, we demonstrate how a programming language, Rely, enables developers to reason about and verify the quantitative reliability of an application – namely, the probability that it produces the correct result when executed on unreliable hardware. Rely leverages a static quantitative reliability analysis that verifies quantitative requirements on the reliability of an application, enabling a developer to perform sound and verified reliability engineering.

Keywords

Probabilistic verificationunreliable hardwarereliability
Type
Chapter
Information
Foundations of Probabilistic Programming , pp. 533 - 568
Publisher: Cambridge University Press
Print publication year: 2020
Creative Commons
Creative Common License - CCCreative Common License - BY
This content is Open Access and distributed under the terms of the Creative Commons Attribution licence CC-BY 4.0 https://creativecommons.org/cclicenses/

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