research-article

An Inexact Ultra-low Power Bio-signal Processing Architecture With Lightweight Error Recovery

Authors:

RubÉn Braojos,

Giovanni Ansaloni,

David AtienzaAuthors Info & Claims

ACM Transactions on Embedded Computing Systems (TECS), Volume 16, Issue 5s

Article No.: 159, Pages 1 - 19

https://doi.org/10.1145/3126565

Published: 27 September 2017 Publication History

Abstract

The energy efficiency of digital architectures is tightly linked to the voltage level (Vdd) at which they operate. Aggressive voltage scaling is therefore mandatory when ultra-low power processing is required. Nonetheless, the lowest admissible Vdd is often bounded by reliability concerns, especially since static and dynamic non-idealities are exacerbated in the near-threshold region, imposing costly guard-bands to guarantee correctness under worst-case conditions. A striking alternative, explored in this paper, waives the requirement for unconditional correctness, undergoing more relaxed constraints. First, after a run-time failure, processing correctly resumes at a later point in time. Second, failures induce a limited Quality-of-Service (QoS) degradation. We focus our investigation on the practical scenario of embedded bio-signal analysis, a domain in which energy efficiency is key, while applications are inherently error-tolerant to a certain degree. Targeting a domain-specific multi-core platform, we present a study of the impact of inexactness on application-visible errors. Then, we introduce a novel methodology to manage them, which requires minimal hardware resources and a negligible energy overhead. Experimental evidence show that, by tolerating 900 errors/hour, the resulting inexact platform can achieve an efficiency increase of up to 24%, with a QoS degradation of less than 3%.

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Cited By

Scarabottolo IAnsaloni GConstantinides GPozzi L(2022)A Formal Framework for Maximum Error Estimation in Approximate Logic SynthesisIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems10.1109/TCAD.2021.307565141:4(840-853)Online publication date: Apr-2022
https://doi.org/10.1109/TCAD.2021.3075651
Ghosh ARaha AMukherjee A(2020)Energy-Efficient IoT-Health Monitoring System using Approximate ComputingInternet of Things10.1016/j.iot.2020.100166(100166)Online publication date: Jan-2020
https://doi.org/10.1016/j.iot.2020.100166
Ferretti LAnsaloni GPozzi LAminifar AAtienza DCammoun LRyvlin P(2019)Tailoring SVM Inference for Resource-Efficient ECG-Based Epilepsy Monitors2019 Design, Automation & Test in Europe Conference & Exhibition (DATE)10.23919/DATE.2019.8714858(948-951)Online publication date: Mar-2019
https://doi.org/10.23919/DATE.2019.8714858
Show More Cited By

Index Terms

An Inexact Ultra-low Power Bio-signal Processing Architecture With Lightweight Error Recovery
1. Applied computing
  1. Life and medical sciences
    1. Health care information systems
2. Computer systems organization

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Published In

cover image ACM Transactions on Embedded Computing Systems

ACM Transactions on Embedded Computing Systems Volume 16, Issue 5s

Special Issue ESWEEK 2017, CASES 2017, CODES + ISSS 2017 and EMSOFT 2017

October 2017

1448 pages

ISSN:1539-9087

EISSN:1558-3465

DOI:10.1145/3145508

Editor:
Sandeep K. Shukla
Indian Institute of Technology, India

Issue’s Table of Contents

Copyright © 2017 ACM.

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ACM Journals for the Design of Smart and Connected Systems

Publication History

Published: 27 September 2017

Accepted: 01 June 2017

Revised: 01 June 2017

Received: 01 April 2017

Published in TECS Volume 16, Issue 5s

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Cited By

Scarabottolo IAnsaloni GConstantinides GPozzi L(2022)A Formal Framework for Maximum Error Estimation in Approximate Logic SynthesisIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems10.1109/TCAD.2021.307565141:4(840-853)Online publication date: Apr-2022
https://doi.org/10.1109/TCAD.2021.3075651
Ghosh ARaha AMukherjee A(2020)Energy-Efficient IoT-Health Monitoring System using Approximate ComputingInternet of Things10.1016/j.iot.2020.100166(100166)Online publication date: Jan-2020
https://doi.org/10.1016/j.iot.2020.100166
Ferretti LAnsaloni GPozzi LAminifar AAtienza DCammoun LRyvlin P(2019)Tailoring SVM Inference for Resource-Efficient ECG-Based Epilepsy Monitors2019 Design, Automation & Test in Europe Conference & Exhibition (DATE)10.23919/DATE.2019.8714858(948-951)Online publication date: Mar-2019
https://doi.org/10.23919/DATE.2019.8714858
Scarabottolo IAnsaloni GPozzi L(2018)Circuit carving: A methodology for the design of approximate hardware2018 Design, Automation & Test in Europe Conference & Exhibition (DATE)10.23919/DATE.2018.8342067(545-550)Online publication date: Mar-2018
https://doi.org/10.23919/DATE.2018.8342067
Surrel GAminifar ARincon FMurali SAtienza D(2018)Online Obstructive Sleep Apnea Detection on Medical Wearable SensorsIEEE Transactions on Biomedical Circuits and Systems10.1109/TBCAS.2018.282465912:4(762-773)Online publication date: Aug-2018
https://doi.org/10.1109/TBCAS.2018.2824659
Basu SDuch LPeon-Quiros MAtienza DAnsaloni GPozzi L(2018)Heterogeneous and Inexact: Maximizing Power Efficiency of Edge Computing Sensors for Health Monitoring Applications2018 IEEE International Symposium on Circuits and Systems (ISCAS)10.1109/ISCAS.2018.8351595(1-5)Online publication date: May-2018
https://doi.org/10.1109/ISCAS.2018.8351595

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