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The Matrix KV Storage System Based on NVM Devices
The storage device based on Nonvolatile Memory (NVM devices) has high read/write speed and embedded processor. It is a useful way to improve the efficiency of Key-Value (KV) application. However it still has some limitations such as limited capacity, poorer computing power compared with CPU, and com...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6562584/ https://www.ncbi.nlm.nih.gov/pubmed/31137767 http://dx.doi.org/10.3390/mi10050346 |
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author | Cai, Tao Chen, Fuli He, Qingjian Niu, Dejiao Wang, Jie |
author_facet | Cai, Tao Chen, Fuli He, Qingjian Niu, Dejiao Wang, Jie |
author_sort | Cai, Tao |
collection | PubMed |
description | The storage device based on Nonvolatile Memory (NVM devices) has high read/write speed and embedded processor. It is a useful way to improve the efficiency of Key-Value (KV) application. However it still has some limitations such as limited capacity, poorer computing power compared with CPU, and complex I/O system software. Thus it is not an effective way to construct KV storage system with NVM devices directly. We analyze the characteristics of NVM devices and demands of KV application to design the matrix KV storage system based on NVM Devices. The group collaboration management based on Bloomfilter, intragroup optimization based on competition, embedded KV management based on B+-tree, and the new interface of KV storage system are presented. Then, the embedded processor in the NVM device and CPU can be comprehensively utilized to construct a matrix KV pair management system. It can improve the storage and management efficiency of massive KV pairs, and it can also support the efficient execution of KV applications. A prototype is implemented named MKVS (the matrix KV storage system based on NVM devices) to test with YCSB (Yahoo! Cloud System Benchmark) and to compare with the current in-memory KV store. The results show that MKVS can improve the throughput by 5.98 times, and reduce the 99.7% read latency and 77.2% write latency. |
format | Online Article Text |
id | pubmed-6562584 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-65625842019-06-17 The Matrix KV Storage System Based on NVM Devices Cai, Tao Chen, Fuli He, Qingjian Niu, Dejiao Wang, Jie Micromachines (Basel) Article The storage device based on Nonvolatile Memory (NVM devices) has high read/write speed and embedded processor. It is a useful way to improve the efficiency of Key-Value (KV) application. However it still has some limitations such as limited capacity, poorer computing power compared with CPU, and complex I/O system software. Thus it is not an effective way to construct KV storage system with NVM devices directly. We analyze the characteristics of NVM devices and demands of KV application to design the matrix KV storage system based on NVM Devices. The group collaboration management based on Bloomfilter, intragroup optimization based on competition, embedded KV management based on B+-tree, and the new interface of KV storage system are presented. Then, the embedded processor in the NVM device and CPU can be comprehensively utilized to construct a matrix KV pair management system. It can improve the storage and management efficiency of massive KV pairs, and it can also support the efficient execution of KV applications. A prototype is implemented named MKVS (the matrix KV storage system based on NVM devices) to test with YCSB (Yahoo! Cloud System Benchmark) and to compare with the current in-memory KV store. The results show that MKVS can improve the throughput by 5.98 times, and reduce the 99.7% read latency and 77.2% write latency. MDPI 2019-05-27 /pmc/articles/PMC6562584/ /pubmed/31137767 http://dx.doi.org/10.3390/mi10050346 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Cai, Tao Chen, Fuli He, Qingjian Niu, Dejiao Wang, Jie The Matrix KV Storage System Based on NVM Devices |
title | The Matrix KV Storage System Based on NVM Devices |
title_full | The Matrix KV Storage System Based on NVM Devices |
title_fullStr | The Matrix KV Storage System Based on NVM Devices |
title_full_unstemmed | The Matrix KV Storage System Based on NVM Devices |
title_short | The Matrix KV Storage System Based on NVM Devices |
title_sort | matrix kv storage system based on nvm devices |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6562584/ https://www.ncbi.nlm.nih.gov/pubmed/31137767 http://dx.doi.org/10.3390/mi10050346 |
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