Storage Class Memory Based Hybrid Memory System for Practical Remote Sensing SCIE SCOPUS

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Title
Storage Class Memory Based Hybrid Memory System for Practical Remote Sensing
Author(s)
Koo, Sungmin; Seo, Jungmin; Song, Yujae; Baek, Seungjae
KIOST Author(s)
Koo, Sungmin(구성민)Seo, Jungmin(서정민)Song, Yujae(송유재)Baek, Seungjae(백승재)
Publication Year
2020-12
Abstract
In the remote sensing domain, large-sized, files such as high-resolution satellite images or sonar video clips from unmanned underwater vehicles are very common. For processing big files, a large main memory is necessary. The main memory capacity highly influences the performance of computer systems. The demand for DRAM capacity has never been satisfied, and more importantly, large DRAM systems suffer from significant power consumption. To ease the problem, a promising solution is to build a hybrid main memory (HMM) system composed of a small number of fast DRAMs and many inexpensive devices. By mimicking large and fast main memory capacity, HMM allows computer systems to run applications that require more DRAM than is installed on the system. In this paper, a novel HMM management scheme for a storage class memory (SCM)-based HMM was introduced. As all the data stored on SCM are already non-volatile, the overall performance of the computer system is enhanced further by not flushing them periodically. The proposed idea was implemented on Linux and its performance was measured using an SCM emulation system. It was shown that HMM efficiently improves performance by up to 77.9 %, compared with a conventional operating system. Additionally, it was demonstrated that the proposed idea's fault recovery mechanisms could restore dirty data that are not yet synchronized with storage, within 91 % of the test time.
ISSN
0749-0208
URI
https://sciwatch.kiost.ac.kr/handle/2020.kiost/38974
DOI
10.2112/si102-031.1
Bibliographic Citation
Journal of Coastal Research, v.102, no.sp1, pp.254 - 260, 2020
Publisher
Coastal Education & Research Foundation, Inc.
Type
Article
Language
English
Document Type
Article
Publisher
Coastal Education & Research Foundation, Inc.
Related Researcher
Research Interests

Computer System,System Software,Storage System,컴퓨터 시스템,시스템 소프트웨어,스토리지 시스템

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