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research article

Exploiting Errors for Efficiency: A Survey from Circuits to Applications

Stanley-Marbell, Phillip
•
Alaghi, Armin
•
Carbin, Michael
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June 1, 2020
Acm Computing Surveys

When a computational task tolerates a relaxation of its specification or when an algorithm tolerates the effects of noise in its execution, hardware, system software, and programming language compilers or their runtime systems can trade deviations from correct behavior for lower resource usage. We present, for the first time, a synthesis of research results on computing systems that only make as many errors as their end-to-end applications can tolerate. The results span the disciplines of computer-aided design of circuits, digital system design, computer architecture, programming languages, operating systems, and information theory. Rather than over-provisioning the resources controlled by each of these layers of abstraction to avoid errors, it can be more efficient to exploit the masking of errors occurring at one layer and thereby prevent those errors from propagating to a higher layer.

We demonstrate the potential benefits of end-to-end approaches using two illustrative examples. We introduce a formalization of terminology that allows us to present a coherent view across the techniques traditionally used by different research communities in their individual layer of focus. Using this formalization, we survey tradeoffs for individual layers of computing systems at the circuit, architecture, operating system, and programming language levels as well as fundamental information-theoretic limits to tradeoffs between resource usage and correctness.

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Type
research article
DOI
10.1145/3394898
Web of Science ID

WOS:000582586400006

Author(s)
Stanley-Marbell, Phillip
Alaghi, Armin
Carbin, Michael
Darulova, Eva  
Dolecek, Lara
Gerstlauer, Andreas
Gillani, Ghayoor
Jevdjic, Djordje  
Moreau, Thierry
Cacciotti, Mattia  
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Date Issued

2020-06-01

Publisher

ASSOC COMPUTING MACHINERY

Published in
Acm Computing Surveys
Volume

53

Issue

3

Start page

51

Subjects

Computer Science, Theory & Methods

•

Computer Science

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approximate computing

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error efficiency

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cross-layer optimization

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neural-networks

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computation

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cost

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architecture

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performance

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accuracy

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design

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limits

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approximation

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reliability

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
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PARSA  
ICLAB  
Available on Infoscience
November 24, 2020
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/173609
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