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Resilience Evaluation for Approximating SystemC Designs Using Machine Learning Techniques

Goli, Mehran and Stoppe, Jannis and Drechsler, Rolf (2018) Resilience Evaluation for Approximating SystemC Designs Using Machine Learning Techniques. In: 2018 International Symposium on Rapid System Prototyping (RSP), pp. 97-103. IEEE. 2018 International Symposium on Rapid System Prototyping (RSP), Torino, Italien. doi: 10.1109/RSP.2018.8631997. ISBN 978-1-5386-7557-1. ISSN 2150-5519.

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Official URL: https://ieeexplore.ieee.org/abstract/document/8631997

Abstract

As digital circuits have become more complicated than ever, abstract description languages such as SystemC have been introduced, allowing designers to work on more abstract levels during the design process. Design metrics such as performance and energy consumption are a central concern for designers at all levels of abstraction. Approximate computing is a promising way to optimize these criteria, sacrificing accuracy. Defining which parts of a design can be approximated (and to what degree) is a crucial and non-trivial design decision, which is usually connected to a larger programming effort, especially when exploring the design space manually. In this paper, we propose an automated approach based on machine learning techniques in order to detect the resilience of a given SystemC design's modules. This is used to identify components of the design that can be approximated. The effectiveness of the proposed method is evaluated using several SystemC benchmarks from various domains.

Item URL in elib:https://elib.dlr.de/141072/
Document Type:Conference or Workshop Item (Speech)
Title:Resilience Evaluation for Approximating SystemC Designs Using Machine Learning Techniques
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Goli, MehranUNSPECIFIEDUNSPECIFIED
Stoppe, Jannisjannis.stoppe (at) dlr.deUNSPECIFIED
Drechsler, RolfUniversität BremenUNSPECIFIED
Date:October 2018
Journal or Publication Title:2018 International Symposium on Rapid System Prototyping (RSP)
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
DOI :10.1109/RSP.2018.8631997
Page Range:pp. 97-103
Publisher:IEEE
ISSN:2150-5519
ISBN:978-1-5386-7557-1
Status:Published
Keywords:Resilience, SystemC, Approximation
Event Title:2018 International Symposium on Rapid System Prototyping (RSP)
Event Location:Torino, Italien
Event Type:international Conference
HGF - Research field:other
HGF - Program:other
HGF - Program Themes:other
DLR - Research area:no assignment
DLR - Program:no assignment
DLR - Research theme (Project):no assignment
Location: Bremerhaven
Institutes and Institutions:Institute for the Protection of Maritime Infrastructures > Maritime Security Technologies
Deposited By: Stoppe, Jannis
Deposited On:25 Feb 2021 09:41
Last Modified:25 Feb 2021 09:41

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