Reliability Optimization under Severe Uncertainty for NoC Based Architectures Using an Info-Gap Decision Approach

Wenkai Guan; Jinhua Zhang; Cristinel Ababei

doi:10.1109/MWSCAS48704.2020.9184673

Reliability Optimization under Severe Uncertainty for NoC Based Architectures Using an Info-Gap Decision Approach

Wenkai Guan, Jinhua Zhang, Cristinel Ababei

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

2 Scopus citations

Abstract

Increased uncertainties in design parameters undermine the accuracy of the mapping of embedded applications to Network-on-Chip (NoC) based manycore architectures. In this paper, we attempt for the first time to apply the info-gap theory to uncertainty modeling in the context of embedded systems design. We first propose a novel info-gap based uncertainty-aware reliability model for NoC based manycore platforms. We then develop an uncertainty-aware solution to the problem of mapping in embedded systems. The solution is implemented as a computer program that can generate robust Pareto frontiers. Simulation results indicate that the proposed info-gap based uncertainty-aware mapping generates Pareto frontiers that have significant differences from the ones obtained with a traditional deterministic approach. Identifying and quantifying these differences is an important first step towards the development of better mapping optimization processes in order to arrive to optimal rather than suboptimal solutions.

Original language	English (US)
Title of host publication	2020 IEEE 63rd International Midwest Symposium on Circuits and Systems, MWSCAS 2020 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	478-481
Number of pages	4
ISBN (Electronic)	9781538629161
DOIs	https://doi.org/10.1109/MWSCAS48704.2020.9184673
State	Published - Aug 2020
Externally published	Yes
Event	63rd IEEE International Midwest Symposium on Circuits and Systems, MWSCAS 2020 - Springfield, United States Duration: Aug 9 2020 → Aug 12 2020

Publication series

Name	Midwest Symposium on Circuits and Systems
Volume	2020-August
ISSN (Print)	1548-3746

Conference

Conference	63rd IEEE International Midwest Symposium on Circuits and Systems, MWSCAS 2020
Country/Territory	United States
City	Springfield
Period	8/9/20 → 8/12/20

Bibliographical note

Funding Information:
ACKNOWLEDGEMENT The authors would like to thank the anonymous reviewers for their feedback, that helped improve our paper. This work was supported by the NSF, grant CCF-1524909. Any findings and conclusions expressed herein are those of the authors and do not necessarily reflect the views of the NSF.

Publisher Copyright:
© 2020 IEEE.

Publisher link

10.1109/MWSCAS48704.2020.9184673

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Guan, W., Zhang, J., & Ababei, C. (2020). Reliability Optimization under Severe Uncertainty for NoC Based Architectures Using an Info-Gap Decision Approach. In 2020 IEEE 63rd International Midwest Symposium on Circuits and Systems, MWSCAS 2020 - Proceedings (pp. 478-481). Article 9184673 (Midwest Symposium on Circuits and Systems; Vol. 2020-August). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/MWSCAS48704.2020.9184673

Reliability Optimization under Severe Uncertainty for NoC Based Architectures Using an Info-Gap Decision Approach. / Guan, Wenkai; Zhang, Jinhua; Ababei, Cristinel.
2020 IEEE 63rd International Midwest Symposium on Circuits and Systems, MWSCAS 2020 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2020. p. 478-481 9184673 (Midwest Symposium on Circuits and Systems; Vol. 2020-August).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Guan, W, Zhang, J & Ababei, C 2020, Reliability Optimization under Severe Uncertainty for NoC Based Architectures Using an Info-Gap Decision Approach. in 2020 IEEE 63rd International Midwest Symposium on Circuits and Systems, MWSCAS 2020 - Proceedings., 9184673, Midwest Symposium on Circuits and Systems, vol. 2020-August, Institute of Electrical and Electronics Engineers Inc., pp. 478-481, 63rd IEEE International Midwest Symposium on Circuits and Systems, MWSCAS 2020, Springfield, United States, 8/9/20. https://doi.org/10.1109/MWSCAS48704.2020.9184673

Guan W, Zhang J, Ababei C. Reliability Optimization under Severe Uncertainty for NoC Based Architectures Using an Info-Gap Decision Approach. In 2020 IEEE 63rd International Midwest Symposium on Circuits and Systems, MWSCAS 2020 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2020. p. 478-481. 9184673. (Midwest Symposium on Circuits and Systems). doi: 10.1109/MWSCAS48704.2020.9184673

Guan, Wenkai ; Zhang, Jinhua ; Ababei, Cristinel. / Reliability Optimization under Severe Uncertainty for NoC Based Architectures Using an Info-Gap Decision Approach. 2020 IEEE 63rd International Midwest Symposium on Circuits and Systems, MWSCAS 2020 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2020. pp. 478-481 (Midwest Symposium on Circuits and Systems).

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abstract = "Increased uncertainties in design parameters undermine the accuracy of the mapping of embedded applications to Network-on-Chip (NoC) based manycore architectures. In this paper, we attempt for the first time to apply the info-gap theory to uncertainty modeling in the context of embedded systems design. We first propose a novel info-gap based uncertainty-aware reliability model for NoC based manycore platforms. We then develop an uncertainty-aware solution to the problem of mapping in embedded systems. The solution is implemented as a computer program that can generate robust Pareto frontiers. Simulation results indicate that the proposed info-gap based uncertainty-aware mapping generates Pareto frontiers that have significant differences from the ones obtained with a traditional deterministic approach. Identifying and quantifying these differences is an important first step towards the development of better mapping optimization processes in order to arrive to optimal rather than suboptimal solutions.",

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Reliability Optimization under Severe Uncertainty for NoC Based Architectures Using an Info-Gap Decision Approach

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