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Application-Oriented Data Migration to Accelerate In-Memory Database on Hybrid Memory

With the advantage of faster data access than traditional disks, in-memory database systems, such as Redis and Memcached, have been widely applied in data centers and embedded systems. The performance of in-memory database greatly depends on the access speed of memory. With the requirement of high b...

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Autores principales: Zhao, Wenze, Du, Yajuan, Zhang, Mingzhe, Liu, Mingyang, Jin, Kailun, Ausavarungnirun, Rachata
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8781036/
https://www.ncbi.nlm.nih.gov/pubmed/35056217
http://dx.doi.org/10.3390/mi13010052
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author Zhao, Wenze
Du, Yajuan
Zhang, Mingzhe
Liu, Mingyang
Jin, Kailun
Ausavarungnirun, Rachata
author_facet Zhao, Wenze
Du, Yajuan
Zhang, Mingzhe
Liu, Mingyang
Jin, Kailun
Ausavarungnirun, Rachata
author_sort Zhao, Wenze
collection PubMed
description With the advantage of faster data access than traditional disks, in-memory database systems, such as Redis and Memcached, have been widely applied in data centers and embedded systems. The performance of in-memory database greatly depends on the access speed of memory. With the requirement of high bandwidth and low energy, die-stacked memory (e.g., High Bandwidth Memory (HBM)) has been developed to extend the channel number and width. However, the capacity of die-stacked memory is limited due to the interposer challenge. Thus, hybrid memory system with traditional Dynamic Random Access Memory (DRAM) and die-stacked memory emerges. Existing works have proposed to place and manage data on hybrid memory architecture in the view of hardware. This paper considers to manage in-memory database data in hybrid memory in the view of application. We first perform a preliminary study on the hotness distribution of client requests on Redis. From the results, we observe that most requests happen on a small portion of data objects in in-memory database. Then, we propose the Application-oriented Data Migration called ADM to accelerate in-memory database on hybrid memory. We design a hotness management method and two migration policies to migrate data into or out of HBM. We take Redis under comprehensive benchmarks as a case study for the proposed method. Through the experimental results, it is verified that our proposed method can effectively gain performance improvement and reduce energy consumption compared with existing Redis database.
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spelling pubmed-87810362022-01-22 Application-Oriented Data Migration to Accelerate In-Memory Database on Hybrid Memory Zhao, Wenze Du, Yajuan Zhang, Mingzhe Liu, Mingyang Jin, Kailun Ausavarungnirun, Rachata Micromachines (Basel) Article With the advantage of faster data access than traditional disks, in-memory database systems, such as Redis and Memcached, have been widely applied in data centers and embedded systems. The performance of in-memory database greatly depends on the access speed of memory. With the requirement of high bandwidth and low energy, die-stacked memory (e.g., High Bandwidth Memory (HBM)) has been developed to extend the channel number and width. However, the capacity of die-stacked memory is limited due to the interposer challenge. Thus, hybrid memory system with traditional Dynamic Random Access Memory (DRAM) and die-stacked memory emerges. Existing works have proposed to place and manage data on hybrid memory architecture in the view of hardware. This paper considers to manage in-memory database data in hybrid memory in the view of application. We first perform a preliminary study on the hotness distribution of client requests on Redis. From the results, we observe that most requests happen on a small portion of data objects in in-memory database. Then, we propose the Application-oriented Data Migration called ADM to accelerate in-memory database on hybrid memory. We design a hotness management method and two migration policies to migrate data into or out of HBM. We take Redis under comprehensive benchmarks as a case study for the proposed method. Through the experimental results, it is verified that our proposed method can effectively gain performance improvement and reduce energy consumption compared with existing Redis database. MDPI 2021-12-29 /pmc/articles/PMC8781036/ /pubmed/35056217 http://dx.doi.org/10.3390/mi13010052 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/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 (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Zhao, Wenze
Du, Yajuan
Zhang, Mingzhe
Liu, Mingyang
Jin, Kailun
Ausavarungnirun, Rachata
Application-Oriented Data Migration to Accelerate In-Memory Database on Hybrid Memory
title Application-Oriented Data Migration to Accelerate In-Memory Database on Hybrid Memory
title_full Application-Oriented Data Migration to Accelerate In-Memory Database on Hybrid Memory
title_fullStr Application-Oriented Data Migration to Accelerate In-Memory Database on Hybrid Memory
title_full_unstemmed Application-Oriented Data Migration to Accelerate In-Memory Database on Hybrid Memory
title_short Application-Oriented Data Migration to Accelerate In-Memory Database on Hybrid Memory
title_sort application-oriented data migration to accelerate in-memory database on hybrid memory
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8781036/
https://www.ncbi.nlm.nih.gov/pubmed/35056217
http://dx.doi.org/10.3390/mi13010052
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