Improving Flash-Based Disk Cache with Lazy Adaptive Replacement

被引:89
作者
Huang, Sai [1 ,2 ,4 ]
Wei, Qingsong [3 ,5 ]
Feng, Dan [1 ,2 ,4 ]
Chen, Jianxi [1 ,2 ,4 ]
Chen, Cheng [3 ,5 ]
机构
[1] Huazhong Univ Sci & Technol, Wuhan Natl Lab Optoelect, Wuhan 430074, Peoples R China
[2] Huazhong Univ Sci & Technol, Sch Comp, Wuhan 430074, Peoples R China
[3] ASTAR, Data Storage Inst, Wuhan, Peoples R China
[4] Huazhong Univ Sci & Technol, 1037 Luoyu Rd, Wuhan 430074, Peoples R China
[5] Data Storage Inst, 2 Fusionopolis Way,08-01 Innovis, Singapore 138634, Singapore
基金
中国国家自然科学基金;
关键词
Algorithms; Design; Performance; Cache algorithm; endurance; flash memory; solid-state drive;
D O I
10.1145/2737832
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
080201 [机械制造及其自动化];
摘要
For years, the increasing popularity of flash memory has been changing storage systems. Flash-based solid-state drives (SSDs) are widely used as a new cache tier on top of hard disk drives (HDDs) to speed up data-intensive applications. However, the endurance problem of flash memory remains a concern and is getting worse with the adoption of MLC and TLC flash. In this article, we propose a novel cache management algorithm for flash-based disk cache named Lazy Adaptive Replacement Cache (LARC). LARC adopts the idea of selective caching to filter out seldom accessed blocks and prevent them from entering cache. This avoids cache pollution and preserves popular blocks in cache for a longer period of time, leading to a higher hit rate. Meanwhile, by avoiding unnecessary cache replacements, LARC reduces the volume of data written to the SSD and yields an SSD-friendly access pattern. In this way, LARC improves the performance and endurance of the SSD at the same time. LARC is self-tuning and incurs little overhead. It has been extensively evaluated by both trace-driven simulations and synthetic benchmarks on a prototype implementation. Our experiments show that LARC outperforms state-of-art algorithms for different kinds of workloads and extends SSD lifetime by up to 15.7 times.
引用
收藏
页数:24
相关论文
共 41 条
[1]
Agrawal Nitin, 2008, P USENIX ANN TECHN C, P57
[2]
[Anonymous], ACM SIGARCH COMPUTER
[3]
[Anonymous], TARGET
[4]
[Anonymous], 2010, P 1 ACM S CLOUD COMP, DOI DOI 10.1145/1807128.1807152
[5]
[Anonymous], 2007, Blktrace user guide
[6]
Appuswamy R., 2013, IEEE 29 S MASS STOR, P1
[7]
Badam Anirudh., 2011, NSDI, P16
[8]
A STUDY OF REPLACEMENT ALGORITHMS FOR A VIRTUAL-STORAGE COMPUTER [J].
BELADY, LA .
IBM SYSTEMS JOURNAL, 1966, 5 (02) :78-&
[9]
SSD Bufferpool Extensions for Database Systems [J].
Canim, Mustafa ;
Mihaila, George A. ;
Bhattacharjee, Bishwaranjan ;
Ross, Kenneth A. ;
Lang, Christian A. .
PROCEEDINGS OF THE VLDB ENDOWMENT, 2010, 3 (02) :1435-1446
[10]
Chen F., 2011, P INT C SUPERCOMPUTI