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Journal Article Dynamic Data Migration in Hybrid Main Memories for In-Memory Big Data Storage
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Authors
Hai Thanh Mai, Kyoung Hyun Park, Hun Soon Lee, Chang Soo Kim, Miyoung Lee, Sung Jin Hur
Issue Date
2014-12
Citation
ETRI Journal, v.36, no.6, pp.988-998
ISSN
1225-6463
Publisher
한국전자통신연구원 (ETRI)
Language
English
Type
Journal Article
DOI
https://dx.doi.org/10.4218/etrij.14.0114.0012
Abstract
For memory-based big data storage, using hybrid memories consisting of both dynamic random-access memory (DRAM) and non-volatile random-access memories (NVRAMs) is a promising approach. DRAM supports low access time but consumes much energy, whereas NVRAMs have high access time but do not need energy to retain data. In this paper, we propose a new data migration method that can dynamically move data pages into the most appropriate memories to exploit their strengths and alleviate their weaknesses. We predict the access frequency values of the data pages and then measure comprehensively the gains and costs of each placement choice based on these predicted values. Next, we compute the potential benefits of all choices for each candidate page to make page migration decisions. Extensive experiments show that our method improves over the existing ones the access response time by as much as a factor of four, with similar rates of energy consumption.
KSP Keywords
Access Time, Big Data Storage, Data migration, Dynamic random-access memory(DRAM), Memory-based, Migration method, Page migration, access frequency, dynamic data, energy consumption, in-memory