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ClusterFetch: A lightweight prefetcher that responds to intensive disk read patterns

Authors
Ryu, JunheeJeong, HaksuLee, DongeunShin, HeonshikKang, Kyungtae
Issue Date
Aug-2015
Publisher
Institute of Electrical and Electronics Engineers Inc.
Keywords
Application loading; ClusterFetch; Disk I/O scheduling; Prefetching
Citation
Proceedings - 2015 IEEE 17th International Conference on High Performance Computing and Communications, 2015 IEEE 7th International Symposium on Cyberspace Safety and Security and 2015 IEEE 12th International Conference on Embedded Software and Systems, HPCC-CSS-ICESS 2015, pp.1051 - 1056
Indexed
OTHER
Journal Title
Proceedings - 2015 IEEE 17th International Conference on High Performance Computing and Communications, 2015 IEEE 7th International Symposium on Cyberspace Safety and Security and 2015 IEEE 12th International Conference on Embedded Software and Systems, HPCC-CSS-ICESS 2015
Start Page
1051
End Page
1056
URI
https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/20550
DOI
10.1109/HPCC-CSS-ICESS.2015.258
Abstract
Application launch and loading times are important determinants of user experience in the personal computing environment. Since these delays largely depend on the performance of secondary storage, they can be reduced by prefetching disk blocks. However, existing prefetching schemes for general workloads incur a significant overhead in analyzing correlations between blocks so as to choose the blocks to prefetch, and, more significantly, these analyses lack accuracy. We propose a lightweight prefetcher called ClusterFetch which records the sequences of I/O requests that are triggered by file requests during launch and loading. When the same application is run again, the disk blocks that correspond to the stored sequences of I/O requests are prefetched when the related files are opened. Experimental results show that ClusterFetch can reduce application launch times by up to 30.9%, and loading times by up to 15.9%. © 2015 IEEE.
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