RDPM: An Extensible Tool for Resilience Design Patterns Modelling

Mohit Kumar; Christian Engelmann

doi:10.1007/978-3-031-06156-1_23

RDPM: An Extensible Tool for Resilience Design Patterns Modelling

Mohit Kumar, Christian Engelmann

Intelligent Systems and Facilities

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

Abstract

Resilience to faults, errors, and failures in extreme-scale high-performance computing (HPC) systems is a critical challenge. Resilience design patterns offer a new, structured hardware and software design approach for improving resilience. While prior work focused on developing performance, reliability, and availability models for resilience design patterns, this paper extends it by providing a Resilience Design Patterns Modeling (RDPM) tool which allows (1) exploring performance, reliability, and availability of each resilience design pattern, (2) offering customization of parameters to optimize performance, reliability, and availability, and (3) allowing investigation of trade-off models for combining multiple patterns for practical resilience solutions.

Original language	English
Title of host publication	Euro-Par 2021
Subtitle of host publication	Parallel Processing Workshops - Euro-Par 2021 International Workshops, 2021, Revised Selected Papers
Editors	Ricardo Chaves, Dora B. Heras, Aleksandar Ilic, Didem Unat, Rosa M. Badia, Andrea Bracciali, Patrick Diehl, Anshu Dubey, Oh Sangyoon, Stephen L. Scott, Laura Ricci
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	283-297
Number of pages	15
ISBN (Print)	9783031061554
DOIs	https://doi.org/10.1007/978-3-031-06156-1_23
State	Published - 2022
Event	27th International Conference on Parallel and Distributed Computing, Euro-Par 2021 - Virtual, Online Duration: Aug 30 2021 → Aug 31 2021

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	13098 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	27th International Conference on Parallel and Distributed Computing, Euro-Par 2021
City	Virtual, Online
Period	08/30/21 → 08/31/21

Funding

Acknowledgements. This work was supported by the U.S. Department of Energy, Office of Science, Office of Advanced Scientific Computing Research, program managers Robinson Pino and Lucy Nowell. This manuscript has been authored by UT-Battelle, LLC under Contract No. DE-AC05-00OR22725 with the U.S. Department of Energy. This work was sponsored by the U.S. Department of Energy’s Office of Advanced Scientific Computing Research. This manuscript has been authored by UT-Battelle, LLC under Contract No. DE-AC05-00OR22725 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/ downloads/doe-public-access-plan).

Funders	Funder number
U.S. Department of Energy
Office of Science
Advanced Scientific Computing Research	DE-AC05-00OR22725

Keywords

Design patterns
High-performance computing
Resilience
Tool

Access to Document

10.1007/978-3-031-06156-1_23

Cite this

Kumar, M., & Engelmann, C. (2022). RDPM: An Extensible Tool for Resilience Design Patterns Modelling. In R. Chaves, D. B. Heras, A. Ilic, D. Unat, R. M. Badia, A. Bracciali, P. Diehl, A. Dubey, O. Sangyoon, S. L. Scott, & L. Ricci (Eds.), Euro-Par 2021: Parallel Processing Workshops - Euro-Par 2021 International Workshops, 2021, Revised Selected Papers (pp. 283-297). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13098 LNCS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-06156-1_23

Kumar, Mohit ; Engelmann, Christian. / RDPM : An Extensible Tool for Resilience Design Patterns Modelling. Euro-Par 2021: Parallel Processing Workshops - Euro-Par 2021 International Workshops, 2021, Revised Selected Papers. editor / Ricardo Chaves ; Dora B. Heras ; Aleksandar Ilic ; Didem Unat ; Rosa M. Badia ; Andrea Bracciali ; Patrick Diehl ; Anshu Dubey ; Oh Sangyoon ; Stephen L. Scott ; Laura Ricci. Springer Science and Business Media Deutschland GmbH, 2022. pp. 283-297 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "Resilience to faults, errors, and failures in extreme-scale high-performance computing (HPC) systems is a critical challenge. Resilience design patterns offer a new, structured hardware and software design approach for improving resilience. While prior work focused on developing performance, reliability, and availability models for resilience design patterns, this paper extends it by providing a Resilience Design Patterns Modeling (RDPM) tool which allows (1) exploring performance, reliability, and availability of each resilience design pattern, (2) offering customization of parameters to optimize performance, reliability, and availability, and (3) allowing investigation of trade-off models for combining multiple patterns for practical resilience solutions.",

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Kumar, M & Engelmann, C 2022, RDPM: An Extensible Tool for Resilience Design Patterns Modelling. in R Chaves, D B. Heras, A Ilic, D Unat, RM Badia, A Bracciali, P Diehl, A Dubey, O Sangyoon, S L. Scott & L Ricci (eds), Euro-Par 2021: Parallel Processing Workshops - Euro-Par 2021 International Workshops, 2021, Revised Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 13098 LNCS, Springer Science and Business Media Deutschland GmbH, pp. 283-297, 27th International Conference on Parallel and Distributed Computing, Euro-Par 2021, Virtual, Online, 08/30/21. https://doi.org/10.1007/978-3-031-06156-1_23

RDPM: An Extensible Tool for Resilience Design Patterns Modelling. / Kumar, Mohit; Engelmann, Christian.
Euro-Par 2021: Parallel Processing Workshops - Euro-Par 2021 International Workshops, 2021, Revised Selected Papers. ed. / Ricardo Chaves; Dora B. Heras; Aleksandar Ilic; Didem Unat; Rosa M. Badia; Andrea Bracciali; Patrick Diehl; Anshu Dubey; Oh Sangyoon; Stephen L. Scott; Laura Ricci. Springer Science and Business Media Deutschland GmbH, 2022. p. 283-297 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13098 LNCS).

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

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Kumar M, Engelmann C. RDPM: An Extensible Tool for Resilience Design Patterns Modelling. In Chaves R, B. Heras D, Ilic A, Unat D, Badia RM, Bracciali A, Diehl P, Dubey A, Sangyoon O, L. Scott S, Ricci L, editors, Euro-Par 2021: Parallel Processing Workshops - Euro-Par 2021 International Workshops, 2021, Revised Selected Papers. Springer Science and Business Media Deutschland GmbH. 2022. p. 283-297. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-031-06156-1_23

RDPM: An Extensible Tool for Resilience Design Patterns Modelling

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