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Significance-Aware Program Execution on Unreliable Hardware

Authors:

Konstantinos Parasyris,

Vassilis Vassiliadis,

Christos D. Antonopoulos,

Nikolaos BellasAuthors Info & Claims

ACM Transactions on Architecture and Code Optimization (TACO), Volume 14, Issue 2

Article No.: 12, Pages 1 - 25

https://doi.org/10.1145/3058980

Published: 28 April 2017 Publication History

Abstract

This article introduces a significance-centric programming model and runtime support that sets the supply voltage in a multicore CPU to sub-nominal values to reduce the energy footprint and provide mechanisms to control output quality. The developers specify the significance of application tasks respecting their contribution to the output quality and provide check and repair functions for handling faults. On a multicore system, we evaluate five benchmarks using an energy model that quantifies the energy reduction. When executing the least-significant tasks unreliably, our approach leads to 20% CPU energy reduction with respect to a reliable execution and has minimal quality degradation.

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Cited By

Fink ZParasyris KRathi PGeorgakoudis GMenon HBremer P(2024)HPAC-ML: A Programming Model for Embedding ML Surrogates in Scientific ApplicationsProceedings of the International Conference for High Performance Computing, Networking, Storage, and Analysis10.1109/SC41406.2024.00078(1-16)Online publication date: 17-Nov-2024
https://dl.acm.org/doi/10.1109/SC41406.2024.00078
Tsiokanos ITompazi SGeorgakoudis GMukhanov LKarakonstantis G(2023)ARETE: Accurate Error Assessment via Machine Learning-Guided Dynamic-Timing AnalysisIEEE Transactions on Computers10.1109/TC.2022.319196672:4(1026-1040)Online publication date: 1-Apr-2023
https://dl.acm.org/doi/10.1109/TC.2022.3191966
Tompazi STsiokanos IMartinez del-Rincon JMukhanov LKarakonstantis G(2022)Instruction-aware Learning-based Timing Error Models through Significance-driven Approximations2022 IEEE 40th International Conference on Computer Design (ICCD)10.1109/ICCD56317.2022.00074(455-462)Online publication date: Oct-2022
https://doi.org/10.1109/ICCD56317.2022.00074
Show More Cited By

Index Terms

Significance-Aware Program Execution on Unreliable Hardware
1. Computer systems organization
  1. Dependable and fault-tolerant systems and networks
    1. Reliability
2. Theory of computation
  1. Semantics and reasoning
    1. Program semantics

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Published In

cover image ACM Transactions on Architecture and Code Optimization

ACM Transactions on Architecture and Code Optimization Volume 14, Issue 2

June 2017

259 pages

ISSN:1544-3566

EISSN:1544-3973

DOI:10.1145/3086564

Editor:
Koen De Bosschere
Ghent University

Issue’s Table of Contents

Copyright © 2017 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 28 April 2017

Accepted: 01 February 2017

Revised: 01 February 2017

Received: 01 August 2016

Published in TACO Volume 14, Issue 2

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Cited By

Fink ZParasyris KRathi PGeorgakoudis GMenon HBremer P(2024)HPAC-ML: A Programming Model for Embedding ML Surrogates in Scientific ApplicationsProceedings of the International Conference for High Performance Computing, Networking, Storage, and Analysis10.1109/SC41406.2024.00078(1-16)Online publication date: 17-Nov-2024
https://dl.acm.org/doi/10.1109/SC41406.2024.00078
Tsiokanos ITompazi SGeorgakoudis GMukhanov LKarakonstantis G(2023)ARETE: Accurate Error Assessment via Machine Learning-Guided Dynamic-Timing AnalysisIEEE Transactions on Computers10.1109/TC.2022.319196672:4(1026-1040)Online publication date: 1-Apr-2023
https://dl.acm.org/doi/10.1109/TC.2022.3191966
Tompazi STsiokanos IMartinez del-Rincon JMukhanov LKarakonstantis G(2022)Instruction-aware Learning-based Timing Error Models through Significance-driven Approximations2022 IEEE 40th International Conference on Computer Design (ICCD)10.1109/ICCD56317.2022.00074(455-462)Online publication date: Oct-2022
https://doi.org/10.1109/ICCD56317.2022.00074
Parasyris KGeorgakoudis GMenon HDiffenderfer JLaguna IOsei-Kuffuor DSchordan Mde Supinski BHall MGamblin T(2021)HPACProceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis10.1145/3458817.3476216(1-14)Online publication date: 14-Nov-2021
https://dl.acm.org/doi/10.1145/3458817.3476216
Maroudas ELalis SBellas NAntonopoulos CPalesi MTumeo AGoumas GAlmudever C(2021)Exploring the potential of context-aware dynamic CPU undervoltingProceedings of the 18th ACM International Conference on Computing Frontiers10.1145/3457388.3458658(73-82)Online publication date: 11-May-2021
https://dl.acm.org/doi/10.1145/3457388.3458658
Tsiokanos IPapadimitriou GGizopoulos DKarakonstantis G(2021)Boosting Microprocessor Efficiency: Circuit- and Workload-Aware Assessment of Timing Errors2021 IEEE International Symposium on Workload Characterization (IISWC)10.1109/IISWC53511.2021.00022(125-137)Online publication date: Nov-2021
https://doi.org/10.1109/IISWC53511.2021.00022
Parasyris KKoutsovasilis PVassiliadis VAntonopoulos CBellas NLalis S(2018)A Framework for Evaluating Software on Reduced Margins Hardware2018 48th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN)10.1109/DSN.2018.00043(330-337)Online publication date: Jun-2018
https://doi.org/10.1109/DSN.2018.00043

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