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The Matrix KV Storage System Based on NVM Devices.

Tao Cai1, Fuli Chen2, Qingjian He3

  • 1School of Computer Science and Communication Engineering, Jiangsu University, Zhenjiang 212013, China. caitao@ujs.edu.cn.

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|May 30, 2019
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Summary
This summary is machine-generated.

This study introduces a matrix Key-Value (KV) storage system using Nonvolatile Memory (NVM) devices. The novel system significantly boosts throughput and reduces latency for KV applications.

Keywords:
I/O system software stackkey value pairs managementkey value storage systemnonvolatile memory

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Area of Science:

  • Computer Science
  • Data Storage Systems
  • Database Management

Background:

  • Nonvolatile Memory (NVM) devices offer high speed but have limitations like capacity and I/O complexity.
  • Directly using NVM devices for Key-Value (KV) storage systems is inefficient due to these limitations.
  • KV applications require efficient storage and management of massive data pairs.

Purpose of the Study:

  • To design an effective matrix KV storage system leveraging NVM devices.
  • To overcome the limitations of NVM devices for KV applications.
  • To improve the storage and management efficiency of massive KV pairs.

Main Methods:

  • Designed a matrix KV storage system by analyzing NVM device characteristics and KV application demands.
  • Implemented group collaboration management using Bloomfilter and intragroup optimization via competition.
  • Developed embedded KV management with B+-tree and a new KV storage interface.
  • Utilized both NVM device embedded processors and CPUs for comprehensive management.

Main Results:

  • A prototype, MKVS (matrix KV storage system based on NVM devices), was implemented and tested.
  • MKVS demonstrated a 5.98x improvement in throughput compared to in-memory KV stores.
  • MKVS achieved a 99.7% reduction in read latency and a 77.2% reduction in write latency.

Conclusions:

  • The matrix KV storage system effectively utilizes NVM devices and CPUs for efficient KV pair management.
  • MKVS significantly enhances storage and management efficiency for massive KV pairs.
  • The system supports efficient execution of KV applications, outperforming current solutions.