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Conference Paper Design of Distributed Memory Integration Framework(DMIf)
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Authors
Shinyoung Ahn, Gyuil Cha, Youngho Kim, Eunji Lim, Seungjo Bae, Won-Young Kim
Issue Date
2016-01
Citation
International Conference on Information Networking (ICOIN) 2016, pp.343-347
Publisher
IEEE
Language
English
Type
Conference Paper
DOI
https://dx.doi.org/10.1109/ICOIN.2016.7427128
Abstract
Big memory applications such as in-memory database, denovo assembly application in the human genome sequencing area, big data analytics, and large scale scientific calculation are increasing explosively. However, the big memory system has been too expensive for many researchers and students. Therefore, methods to harvest remotely distributed memory has been considered as a cost effective way to run big memory applications in the cluster environment where computing nodes are connected via high speed network. We designed and implemented a new framework, DMIf(Distributed Memory Integrated framework), which harvests idle memory of distributed nodes in a cluster and serves it to the big memory application. The collected distributed memory will provide faster data processing in a cost-effective way for the big-data/memory application.
KSP Keywords
Data processing, DeNovo Assembly, High-speed networks, Human genome, Integrated framework, Memory System, Memory applications, Scientific calculation, big data analytics, cost-effective, distributed memory