ETRI-Knowledge Sharing Plaform

ENGLISH

성과물

논문 검색
구분 SCI
연도 ~ 키워드

상세정보

학술대회 Design of Distributed Memory Integration Framework(DMIf)
Cited 3 time in scopus Download 2 time Share share facebook twitter linkedin kakaostory
저자
안신영, 차규일, 차규일, 임은지, 배승조, 김원영
발행일
201601
출처
International Conference on Information Networking (ICOIN) 2016, pp.343-347
DOI
https://dx.doi.org/10.1109/ICOIN.2016.7427128
협약과제
15MS3300, 유전체 분석용 슈퍼컴퓨팅 시스템 개발, 최완
초록
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 제안 키워드
Big Data Analytics(BDA), Data processing, DeNovo Assembly, Genome sequencing, High speed network, Memory System, Memory applications, Scientific calculation, cost-effective, distributed memory, human genome