상세정보
학술지
Dynamic Data Migration in Hybrid Main Memories for In-Memory Big Data Storage
- 발행일
- 201412
- 출처
- ETRI Journal, v.36 no.6, pp.988-998
- ISSN
- 1225-6463
- 출판사
- 한국전자통신연구원 (ETRI)
- 협약과제
- 13VS3400, 차세대 메모리 기반의 빅데이터 분석 관리 소프트웨어 원천기술 개발, 허성진
- 초록
- 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 제안 키워드
- 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