메뉴 건너뛰기
.. 내서재 .. 알림
소속 기관/학교 인증
인증하면 논문, 학술자료 등을  무료로 열람할 수 있어요.
한국대학교, 누리자동차, 시립도서관 등 나의 기관을 확인해보세요
(국내 대학 90% 이상 구독 중)
로그인 회원가입 고객센터 ENG
주제분류

추천
검색
질문

논문 기본 정보

자료유형
학술저널
저자정보
Yeonwoo Jeong (Sogang University) Gyeonghwan Jung (Sogang University) Kyuli Park (Sogang University) Youngjae Kim (Sogang University) Sungyong Park (Sogang University)
저널정보
대한전자공학회 JOURNAL OF SEMICONDUCTOR TECHNOLOGY AND SCIENCE Journal of Semiconductor Technology and Science Vol.23 No.5
발행연도
2023.10
수록면
273 - 282 (10page)
DOI
10.5573/JSTS.2023.23.5.273

이용수

표지
📌
연구주제
📖
연구배경
🔬
연구방법
🏆
연구결과
AI에게 요청하기
추천
검색
질문

초록· 키워드

오류제보하기
Disaggregated Cloud Memory (DCM) is a hypervisor-based solution that allows client node to extend local memory by leveraging underutilized memory from remote node. These two nodes are generally connected through Remote Direct Memory Access (RDMA)-based high-bandwidth InfiniBand networks. DCM has been a viable alternative to mitigate the performance degradation of memoryintensive applications in memory-constrained environments. There has also been a growing interest in developing memory-intensive applications with managed languages (we call managed applications) such as Java and Python. These managed languages are easy to use but introduce unpredictability in memory usage at runtime. Despite the advantage of memory extension in DCM, the empirical studies that analyze the performance impact and overhead of running managed applications in DCM are lacking. This paper presents the results of a comprehensive study of DCM on both managed and unmanaged applications. The experimental results revealed that the performance degradation of unmanaged applications in DCM is only less than 6% due to fast remote paging and optimized page eviction policy. However, Garbage Collection (GC) severely degrades the performance of managed applications when page fault occurs, while DCM mitigates the performance degradation efficiently.

목차

Abstract
I. INTRODUCTION
II. BACKGROUND
III. EVALUATION
IV. CONCLUSION
REFERENCES

참고문헌 (19)

참고문헌 신청

함께 읽어보면 좋을 논문

논문 유사도에 따라 DBpia 가 추천하는 논문입니다. 함께 보면 좋을 연관 논문을 확인해보세요!

이 논문의 저자 정보

최근 본 자료

전체보기

댓글(0)

0

UCI(KEPA) : I410-151-24-02-088307531