research-article

Nap: Persistent Memory Indexes for NUMA Architectures

Authors:

Jiwu ShuAuthors Info & Claims

ACM Transactions on Storage (TOS), Volume 18, Issue 1

Article No.: 2, Pages 1 - 35

https://doi.org/10.1145/3507922

Published: 29 January 2022 Publication History

Abstract

We present Nap, a black-box approach that converts concurrent persistent memory (PM) indexes into non-uniform memory access (NUMA)-aware counterparts. Based on the observation that real-world workloads always feature skewed access patterns, Nap introduces a NUMA-aware layer (NAL) on the top of existing concurrent PM indexes, and steers accesses to hot items to this layer. The NAL maintains (1) per-node partial views in PM for serving insert/update/delete operations with failure atomicity and (2) a global view in DRAM for serving lookup operations. The NAL eliminates remote PM accesses to hot items without inducing extra local PM accesses. Moreover, to handle dynamic workloads, Nap adopts a fast NAL switch mechanism. We convert five state-of-the-art PM indexes using Nap. Evaluation on a four-node machine with Optane DC Persistent Memory shows that Nap can improve the throughput by up to 2.3× and 1.56× under write-intensive and read-intensive workloads, respectively.

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Index Terms

Nap: Persistent Memory Indexes for NUMA Architectures
1. Hardware
  1. Integrated circuits
    1. Semiconductor memory
      1. Non-volatile memory
2. Information systems
  1. Data management systems
    1. Data structures

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Published In

cover image ACM Transactions on Storage

ACM Transactions on Storage Volume 18, Issue 1

February 2022

245 pages

ISSN:1553-3077

EISSN:1553-3093

DOI:10.1145/3512348

Editor:
Sam H. Noh
Ulsan National Institute of Science and Technology, Ulsan, Republic of Korea

Issue’s Table of Contents

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 29 January 2022

Accepted: 01 December 2021

Revised: 01 December 2021

Received: 01 October 2021

Published in TOS Volume 18, Issue 1

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National Key Research & Development Program of China
National Natural Science Foundation of China
Huawei

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https://dl.acm.org/doi/10.1145/3638770
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Wang RHao YHu LLi XChen MMiao YHumar I(2024)Efficient Crowd Counting via Dual Knowledge DistillationIEEE Transactions on Image Processing10.1109/TIP.2023.334360933(569-583)Online publication date: 1-Jan-2024
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Ge JZhang HShi BLuo YGuo YChai YChen YPan A(2023)SALI: A Scalable Adaptive Learned Index Framework based on Probability ModelsProceedings of the ACM on Management of Data10.1145/36267521:4(1-25)Online publication date: 12-Dec-2023
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An HWang FFeng DZou XLiu ZZhang J(2023)Marlin: A Concurrent and Write-Optimized B+-tree Index on Disaggregated MemoryProceedings of the 52nd International Conference on Parallel Processing10.1145/3605573.3605576(695-704)Online publication date: 13-Sep-2023
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Chen YJhong SHsia C(2023)Roadside Unit-based Unknown Object Detection in Adverse Weather Conditions for Smart Internet of VehiclesACM Transactions on Management Information Systems10.1145/355492313:4(1-21)Online publication date: 3-Jan-2023
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