Analysis on hybrid memory architecture for big data application

Xin LI; Xuan CHEN; Zhiqiu HUANG

doi:10.11959/j.issn.2096-0271.2018031

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Analysis on hybrid memory architecture for big data application

STUDY | 更新时间：2024-06-03

- Analysis on hybrid memory architecture for big data application
- Big Data Research Vol. 4, Issue 3, Pages: 2018031(2018)
- 作者机构：
  
  1. 南京航空航天大学计算机科学与技术学院，江苏南京 211106
  2. 南京航空航天大学自动化学院，江苏南京 211106
- 作者简介：
- 基金信息：
- DOI：10.11959/j.issn.2096-0271.2018031
  CLC： TP302.7
- Online First：2018-05，
  
  Published：15 May 2018
- 稿件说明：
移动端阅览
Xin LI, Xuan CHEN, Zhiqiu HUANG. Analysis on hybrid memory architecture for big data application[J]. Big Data Research, 2018, 4(3): 2018031.
DOI：

Xin LI, Xuan CHEN, Zhiqiu HUANG. Analysis on hybrid memory architecture for big data application[J]. Big Data Research, 2018, 4(3): 2018031. DOI： 10.11959/j.issn.2096-0271.2018031.

摘要

受限于DRAM的扩展性，大数据分析及相关应用性能难以有效提升。新型非易失性存储器凭借其非易失性、高存储密度、低能耗等优点，为大数据应用的性能与效率提升带来了契机。以新型非易失性存储器为基础，阐述PCM/DRAM混合存储架构，通过对该混合存储架构在性能优化、能耗优化、内存管理策略等方面的综述分析，详述了混合存储架构在大数据应用方面的优势及可行性，总结了现有研究工作的缺陷，展望了PCM/DRAM混合内存后续的研究方向。

Abstract

Due to the limited scalability of DRAM

it is hard to optimize the performance of big data analysis and the big data applications.The new non-volatile memory (NVM) brings the opportunity to improve the performance and efficiency for big data applications

which benefits by the advantages of NVM

including its non-volatile

high storage density

and low power consumption.The PCM/DRAM hybrid memory architecture based on the non-volatile memory was analyzed.The feasibility and advantages of hybrid memory for big data applications through the analysis on the optimization of performance

energy consumption and memory management strategies for hybrid memory architecture were demonstrated.The defects in existing work were summarized and the potential research field in PCM/DRAM hybrid memory architecture was discussed.

关键词

Keywords

references

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