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Drop It In Like It's Hot: An Analysis of Persistent Memory as a Drop-in Replacement for NVMe SSDs

Authors:

Maximilian Böther,

Lawrence Benson,

Tilmann RablAuthors Info & Claims

DAMON '21: Proceedings of the 17th International Workshop on Data Management on New Hardware

Article No.: 7, Pages 1 - 8

https://doi.org/10.1145/3465998.3466010

Published: 20 June 2021 Publication History

Abstract

Solid-state drives (SSDs) have improved database system performance significantly due to the higher bandwidth that they provide over traditional hard disk drives. Persistent memory (PMem) is a new storage technology that offers DRAM-like speed at SSD-like capacity. Due to its byte-addressability, research has mainly treated PMem as a replacement of, or an addition to DRAM, e.g., by proposing highly-optimized, DRAM-PMem-hybrid data structures and system designs. However, PMem can also be used via a regular file system interface and standard Linux I/O operations. In this paper, we analyze PMem as a drop-in replacement for Non-Volatile Memory Express (NVMe) SSDs and evaluate possible performance gains while requiring no or only minor changes to existing applications. This drop-in approach speeds-up database systems like Postgres, without requiring any code changes. We systematically evaluate PMem and NVMe SSDs in three database microbenchmarks and the widely used TPC-H benchmark on Postgres. Our experiments show that PMem outperforms a RAID of four NVMe SSDs in read-intensive OLAP workloads by up to 4x without any modifications while achieving similar performance in write-intensive workloads. Finally, we give four practical insights to aid decision-making on when to use PMem as an SSD drop-in replacement and how to optimize for it.

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Koutsoukos DBhartia RFriedman MKlimovic AAlonso G(2023)NVM: Is it Not Very Meaningful for Databases?Proceedings of the VLDB Endowment10.14778/3603581.360358616:10(2444-2457)Online publication date: 1-Jun-2023
https://dl.acm.org/doi/10.14778/3603581.3603586
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cover image ACM Conferences

DAMON '21: Proceedings of the 17th International Workshop on Data Management on New Hardware

June 2021

104 pages

ISBN:9781450385565

DOI:10.1145/3465998

Copyright © 2021 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Published: 20 June 2021

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DAMON '21 Paper Acceptance Rate 15 of 17 submissions, 88%;

Overall Acceptance Rate 94 of 127 submissions, 74%

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Cited By

Sun HKong DJiang SYue YQin X(2024)TrieKV: A High-Performance Key-Value Store Design With Memory as Its First-Class CitizenIEEE Transactions on Parallel and Distributed Systems10.1109/TPDS.2024.347301335:12(2479-2496)Online publication date: Dec-2024
https://doi.org/10.1109/TPDS.2024.3473013
Gupta JDas SKant K(2024)NeSt: A QoS differentiating end-to-end networked storage simulatorComputer Networks10.1016/j.comnet.2024.110833254(110833)Online publication date: Dec-2024
https://doi.org/10.1016/j.comnet.2024.110833
Koutsoukos DBhartia RFriedman MKlimovic AAlonso G(2023)NVM: Is it Not Very Meaningful for Databases?Proceedings of the VLDB Endowment10.14778/3603581.360358616:10(2444-2457)Online publication date: 1-Jun-2023
https://dl.acm.org/doi/10.14778/3603581.3603586
Sun JMa HZhang LLiu HShi HLuo SWu KBruhwiler KZhu CNie YChen JZhang LLiang Y(2023)Accelerating Cloud-Native Databases with Distributed PMem Stores2023 IEEE 39th International Conference on Data Engineering (ICDE)10.1109/ICDE55515.2023.00233(3043-3057)Online publication date: Apr-2023
https://doi.org/10.1109/ICDE55515.2023.00233
Benson LPapke LRabl T(2022)PerMA-benchProceedings of the VLDB Endowment10.14778/3551793.355180715:11(2463-2476)Online publication date: 1-Jul-2022
https://dl.acm.org/doi/10.14778/3551793.3551807
Islam AYork CDai D(2022)A performance study of optane persistent memory: from storage data structures' perspectiveCCF Transactions on High Performance Computing10.1007/s42514-022-00123-x4:4(370-393)Online publication date: 24-Sep-2022
https://doi.org/10.1007/s42514-022-00123-x
Fridman YSnir YRusanovsky MZvi KLevin HHendler DAttiya HOren G(2021)Assessing the Use Cases of Persistent Memory in High-Performance Scientific Computing2021 IEEE/ACM 11th Workshop on Fault Tolerance for HPC at eXtreme Scale (FTXS)10.1109/FTXS54580.2021.00006(11-20)Online publication date: Nov-2021
https://doi.org/10.1109/FTXS54580.2021.00006

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