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Transitioning scientific applications to using non-volatile memory for resilience

Authors:

Brandon Nesterenko,

Jiange ZhangAuthors Info & Claims

MEMSYS '19: Proceedings of the International Symposium on Memory Systems

Pages 114 - 125

https://doi.org/10.1145/3357526.3357563

Published: 30 September 2019 Publication History

Abstract

Scientific applications often run for long periods of time, and as a result, frequently save their internal states to storage media in cases of unexpected interruptions (e.g., hardware failures). Emerging non-volatile memory (NVRAM) can write up to 40× faster than traditional mechanical storage devices, providing an attractive medium for this purpose. This paper investigates the implications of transitioning a scientific application, Fluidanimate, to use NVRAM for fault tolerance. In particular, we evaluate the performance implications and ease-of-use of four fault-tolerance approaches: 1) logging through transactions, 2) multi-versioning through copy-on-write operations, and 3) checkpointing through IO operations (e.g., fwrite) on a direct access (DAX) filesystem and 4) checkpointing with a DRAM cache. Our study results in three key findings. First, additional changes to the application are required to take advantage of the increase in IO speed provided by NVRAM. Second, the performance scalability of the approaches lack when considering a single process. Third, NVRAM can increase reliability in a distributed computing environment by allowing individual nodes to error and automatically recover before the rest of the system notices.

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Cited By

Khan ASim HVazhkudai SKim Y(2021)MOSIQS: Persistent Memory Object Storage With Metadata Indexing and Querying for Scientific ComputingIEEE Access10.1109/ACCESS.2021.30875029(85217-85231)Online publication date: 2021
https://doi.org/10.1109/ACCESS.2021.3087502
Khan ASim HVazhkudai SMa JOh MKim Y(2020)Persistent Memory Object Storage and Indexing for Scientific Computing2020 IEEE/ACM Workshop on Memory Centric High Performance Computing (MCHPC)10.1109/MCHPC51950.2020.00006(1-9)Online publication date: Nov-2020
https://doi.org/10.1109/MCHPC51950.2020.00006

Index Terms

Transitioning scientific applications to using non-volatile memory for resilience

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MEMSYS '19: Proceedings of the International Symposium on Memory Systems

September 2019

517 pages

ISBN:9781450372060

DOI:10.1145/3357526

Copyright © 2019 ACM.

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MEMSYS '19: The International Symposium on Memory Systems

September 30 - October 3, 2019

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Cited By

Khan ASim HVazhkudai SKim Y(2021)MOSIQS: Persistent Memory Object Storage With Metadata Indexing and Querying for Scientific ComputingIEEE Access10.1109/ACCESS.2021.30875029(85217-85231)Online publication date: 2021
https://doi.org/10.1109/ACCESS.2021.3087502
Khan ASim HVazhkudai SMa JOh MKim Y(2020)Persistent Memory Object Storage and Indexing for Scientific Computing2020 IEEE/ACM Workshop on Memory Centric High Performance Computing (MCHPC)10.1109/MCHPC51950.2020.00006(1-9)Online publication date: Nov-2020
https://doi.org/10.1109/MCHPC51950.2020.00006

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