research-article

Persistent Memory I/O Primitives

Authors:

Alexander van Renen,

Thomas Neumann,

Alfons KemperAuthors Info & Claims

DaMoN'19: Proceedings of the 15th International Workshop on Data Management on New Hardware

Article No.: 12, Pages 1 - 7

https://doi.org/10.1145/3329785.3329930

Published: 01 July 2019 Publication History

Abstract

I/O latency and throughput is one of the major performance bottlenecks for disk-based database systems. Upcoming persistent memory (PMem) technologies, like Intel's Optane DC Persistent Memory Modules, promise to bridge the gap between NAND-based flash (SSD) and DRAM, and thus eliminate the I/O bottleneck. In this paper, we provide one of the first performance evaluations of PMem in terms of bandwidth and latency. Based on the results, we develop guidelines for efficient PMem usage and two essential I/O primitives tuned for PMem: log writing and block flushing.

References

[1]

PMDK: Persistent memory development kit. http://www.pmem.io. Accessed: 2019-03-26.

[2]

M. Andrei, C. Lemke, G. Radestock, R. Schulze, C. Thiel, R. Blanco, A. Meghlan, M. Sharique, S. Seifert, S. Vishnoi, D. Booss, T. Peh, I. Schreter, W. Thesing, M. Wagle, and T. Willhalm. SAP HANA adoption of non-volatile memory. PVLDB, 10(12):1754--1765, 2017.

Digital Library

[3]

J. Arulraj, J. J. Levandoski, U. F. Minhas, and P. Larson. Bztree: A high-performance latch-free range index for non-volatile memory. PVLDB, 11(5):553--565, 2018.

[4]

J. Arulraj and A. Pavlo. How to build a non-volatile memory database management system. In SIGMOD, 2017.

Digital Library

[5]

J. Arulraj, A. Pavlo, and S. Dulloor. Let's talk about storage & recovery methods for non-volatile memory database systems. In SIGMOD, pages 707--722, 2015.

Digital Library

[6]

J. Arulraj, A. Pavlo, and K. T. Malladi. Multi-tier buffer management and storage system design for non-volatile memory. arXiv, 2019.

[7]

J. Arulraj, M. Perron, and A. Pavlo. Write-behind logging. PVLDB, 10(4):337--348, 2016.

Digital Library

[8]

M. Canim, G. A. Mihaila, B. Bhattacharjee, K. A. Ross, and C. A. Lang. SSD bufferpool extensions for database systems. PVLDB, 3(2):1435--1446, 2010.

Digital Library

[9]

S. Chen and Q.Jin. Persistent B+-trees in non-volatile main memory. PVLDB, 8(7):786--797, 2015.

Digital Library

[10]

B. F. Cooper, A. Silberstein, E.Tam, R. Ramakrishnan, and R. Sears. Benchmarking cloud serving systems with YCSB. In SoCC, pages 143--154, 2010.

Digital Library

[11]

J. Do, D. Zhang, J. M. Patel, D. J. DeWitt, J. F. Naughton, and A. Halverson. Turbocharging DBMS buffer pool using SSDs. In SIGMOD, 2011.

Digital Library

[12]

S. R. Dulloor, S. Kumar, A. Keshavamurthy, P. Lantz, D. Reddy, R. Sankaran, and J. Jackson. System software for persistent memory. In EuroSys, 2014.

Digital Library

[13]

R. Fang, H. Hsiao, B. He, C. Mohan, and Y. Wang. High performance database logging using storage class memory. In ICDE, pages 1221--1231, 2011.

Digital Library

[14]

P. Götze, S. Baumann, and K. Sattler. An NVM-aware storage layout for analytical workloads. In ICDE Workshops, 2018.

[15]

P. Götze, A. van Renen, L. Lersch, V. Leis, and I. Oukid. Data management on non-volatile memory: A perspective. Datenbank-Spektrum, 18(3), 2018.

[16]

J. Huang, K. Schwan, and M. K. Qureshi. NVRAM-aware logging in transaction systems. PVLDB, 8(4):389--400, 2014.

Digital Library

[17]

J. Izraelevitz, J. Yang, L. Zhang, J. Kim, X. Liu, A. Memaripour, Y. J. Soh, Z. Wang, Y. Xu, S. R. Dulloor, J. Zhao, and S. Swanson. Basic performance measurements of the intel optane DC persistent memory module. CoRR, 2019.

[18]

W. Kang, S. Lee, and B. Moon. Flash as cache extension for online transactional workloads. VLDB Journal, 25(5):673--694, 2016.

Digital Library

[19]

T. Karnagel, R. Dementiev, R. Rajwar, K. Lai, T. Legler, B. Schlegel, and W. Lehner. Improving in-memory database index performance with intel transactional synchronization extensions. In HPCA, 2014.

[20]

H. Kimura. FOEDUS: OLTP engine for a thousand cores and NVRAM. In SIGMOD, pages 691--706, 2015.

Digital Library

[21]

S. K. Lee, K. H. Lim, H. Song, B. Nam, and S. H. Noh. WORT: write optimal radix tree for persistent memory storage systems. In FAST, pages 257--270, 2017.

Digital Library

[22]

X. Liu and K. Salem. Hybrid storage management for database systems. PVLDB, 6(8):541--552, 2013.

Digital Library

[23]

T. Luo, R. Lee, M. P. Mesnier, F. Chen, and X. Zhang. hStorage-DB: Heterogeneity-aware data management to exploit the full capability of hybrid storage systems. PVLDB, 5(10):1076--1087, 2012.

Digital Library

[24]

I. Oukid, D. Booss, W. Lehner, P. Bumbulis, and T. Willhalm. SOFORT: a hybrid SCM-DRAM storage engine for fast data recovery. In DaMoN, 2014.

Digital Library

[25]

I. Oukid, D. Booss, A. Lespinasse, W. Lehner, T. Willhalm, and G. Gomes. Memory management techniques for large-scale persistent-main-memory systems. PVLDB, 2017.

Digital Library

[26]

I. Oukid, J. Lasperas, A. Nica, T. Willhalm, and W. Lehner. FPTree: A hybrid SCM-DRAM persistent and concurrent B-tree for storage class memory. In SIGMOD, pages 371--386, 2016.

Digital Library

[27]

I. Oukid and W. Lehner. Data structure engineering for byte-addressable non-volatile memory. In SIGMOD, 2017.

Digital Library

[28]

I. Oukid, W. Lehner, T. Kissinger, T. Willhalm, and P. Bumbulis. Instant recovery for main memory databases. In CIDR, 2015.

[29]

I. Oukid and L. Lersch. On the diversity of memory and storage technologies. Datenbank-Spektrum, 18(2), 2018.

[30]

I. Oukid, A. Nica, D. D. S. Bossle, W. Lehner, P. Bumbulis, and T. Willhalm. Adaptive recovery for scm-enabled databases. In ADMS, 2017.

[31]

S. Pelley, T. F. Wenisch, B. T. Gold, and B. Bridge. Storage management in the NVRAM era. PVLDB, 2013.

Digital Library

[32]

C. Sauer. Modern techniques for transaction-oriented database recovery. PhD thesis, Kaiserslautern University of Technology, Germany, 2017.

[33]

A. van Renen, V. Leis, A. Kemper, T. Neumann, T. Hashida, K. Oe, Y. Doi, L. Harada, and M. Sato. Managing non-volatile memory in database systems. In SIGMOD, 2018.

Digital Library

[34]

S. Venkataraman, N. Tolia, P. Ranganathan, and R. H. Campbell. Consistent and durable data structures for non-volatile byte-addressable memory. In FAST, pages 61--75, 2011.

Digital Library

[35]

T. Wang and R. Johnson. Scalable logging through emerging non-volatile memory. PVLDB, 7(10):865--876, 2014.

Digital Library

[36]

F. Xia, D. Jiang, J. Xiong, and N. Sun. Hikv: A hybrid index key-value store for DRAM-NVM memory systems. In USENIX ATC, pages 349--362, 2017.

Digital Library

[37]

J. Yang, Q. Wei, C. Chen, C. Wang, K. L. Yong, and B. He. NV-Tree: Reducing consistency cost for NVM-based single level systems. In FAST, pages 167--181, 2015.

Digital Library

Cited By

Baumstark AJibril MSattler K(2025)Hybrid Transactional/Analytical Graph Processing in Modern Memory HierarchiesScalable Data Management for Future Hardware10.1007/978-3-031-74097-8_4(91-116)Online publication date: 24-Jan-2025
https://doi.org/10.1007/978-3-031-74097-8_4
Tamimi SBernhardt AStock FPetrov IKoch A(2024)DANSEN: Database Acceleration on Native Computational Storage by Exploiting NDPACM Transactions on Reconfigurable Technology and Systems10.1145/365562518:1(1-33)Online publication date: 17-Dec-2024
https://dl.acm.org/doi/10.1145/3655625
Trivedi AJansen MDoekemeijer KTalluri STehrany N(2024) Reviving Storage Systems Education in the 21 st Century — An experience report 2024 IEEE 24th International Symposium on Cluster, Cloud and Internet Computing (CCGrid)10.1109/CCGrid59990.2024.00074(616-625)Online publication date: 6-May-2024
https://doi.org/10.1109/CCGrid59990.2024.00074
Show More Cited By

Recommendations

Using DRAM Buffer to Reduce Persistence and Consistence Overheads of Persistent Memory

Persistent memory has the potential to become universal storage for memory and storage uses. Unfortunately, our system architecture is good fit for two-level storage model with DRAM and storage. It incurs two of important performance overheads. First is ...
System-level impacts of persistent main memory using a search engine

Computer memory systems traditionally use distinct technologies for different hierarchy levels, typically volatile, high speed, high cost/byte solid state memory for caches and main memory (SRAM and DRAM), and non-volatile, low speed, low cost/byte ...
How Persistent Memory Will Change Software Systems

Persistent memory promises to be byte addressable, fast, and nonvolatile as well as provide higher capacity and more efficient power consumption. System applications designers stand to gain much from these features, but some work is necessary to fully ...

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences

DaMoN'19: Proceedings of the 15th International Workshop on Data Management on New Hardware

July 2019

150 pages

ISBN:9781450368018

DOI:10.1145/3329785

Copyright © 2019 ACM.

Publication rights licensed to ACM. ACM acknowledges that this contribution was authored or co-authored by an employee, contractor or affiliate of a national government. As such, the Government retains a nonexclusive, royalty-free right to publish or reproduce this article, or to allow others to do so, for Government purposes only.

Sponsors

SIGMOD: ACM Special Interest Group on Management of Data

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 July 2019

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Qualifiers

Research-article
Research
Refereed limited

Conference

SIGMOD/PODS '19

Sponsor:

SIGMOD

SIGMOD/PODS '19: International Conference on Management of Data

July 1, 2019

Amsterdam, Netherlands

Acceptance Rates

Overall Acceptance Rate 94 of 127 submissions, 74%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

52
Total Citations
View Citations
857
Total Downloads

Downloads (Last 12 months)43
Downloads (Last 6 weeks)7

Reflects downloads up to 16 Feb 2025

Other Metrics

View Author Metrics

Citations

Cited By

Baumstark AJibril MSattler K(2025)Hybrid Transactional/Analytical Graph Processing in Modern Memory HierarchiesScalable Data Management for Future Hardware10.1007/978-3-031-74097-8_4(91-116)Online publication date: 24-Jan-2025
https://doi.org/10.1007/978-3-031-74097-8_4
Tamimi SBernhardt AStock FPetrov IKoch A(2024)DANSEN: Database Acceleration on Native Computational Storage by Exploiting NDPACM Transactions on Reconfigurable Technology and Systems10.1145/365562518:1(1-33)Online publication date: 17-Dec-2024
https://dl.acm.org/doi/10.1145/3655625
Trivedi AJansen MDoekemeijer KTalluri STehrany N(2024) Reviving Storage Systems Education in the 21 st Century — An experience report 2024 IEEE 24th International Symposium on Cluster, Cloud and Internet Computing (CCGrid)10.1109/CCGrid59990.2024.00074(616-625)Online publication date: 6-May-2024
https://doi.org/10.1109/CCGrid59990.2024.00074
Williams RMay ZBrown C(2024)End-to-End Trajectory Optimization Using Copernicus and Program to Optimize Simulated Trajectories II2024 IEEE Aerospace Conference10.1109/AERO58975.2024.10521089(1-8)Online publication date: 2-Mar-2024
https://doi.org/10.1109/AERO58975.2024.10521089
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
Desnoyers PAdams IEstro TGandhi AKuenning GMesnier MWaldspurger CWildani AZadok E(2023)Persistent Memory Research in the Post-Optane EraProceedings of the 1st Workshop on Disruptive Memory Systems10.1145/3609308.3625268(23-30)Online publication date: 23-Oct-2023
https://dl.acm.org/doi/10.1145/3609308.3625268
Raina ALu JCidon AFreedman MAamodt TJerger NSwift M(2023)Efficient Compactions between Storage Tiers with PrismDBProceedings of the 28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 310.1145/3582016.3582052(179-193)Online publication date: 25-Mar-2023
https://dl.acm.org/doi/10.1145/3582016.3582052
Islam ADai DMohror KArnold DBadia R(2023)DGAP: Efficient Dynamic Graph Analysis on Persistent MemoryProceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis10.1145/3581784.3607106(1-13)Online publication date: 12-Nov-2023
https://dl.acm.org/doi/10.1145/3581784.3607106
Chen QHu HDeng CLiu DLi STang BYao TXia W(2023)EEPH: An Efficient Extendible Perfect Hashing for Hybrid PMem-DRAM2023 IEEE 39th International Conference on Data Engineering (ICDE)10.1109/ICDE55515.2023.00109(1366-1378)Online publication date: Apr-2023
https://doi.org/10.1109/ICDE55515.2023.00109
Benson LPapke LRabl T(2022)PerMA-benchProceedings of the VLDB Endowment10.14778/3551793.355180715:11(2463-2476)Online publication date: 29-Sep-2022
https://dl.acm.org/doi/10.14778/3551793.3551807
Show More Cited By

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Figures

Tables

Media

View Table of Conten