DiskSeen: Exploiting Disk Layout and Access History to Enhance I/O Prefetch

Xiaoning Ding, Song Jiang, Feng Chen, Kei Davis, Xiaodong Zhang

Research output: Contribution to conferencePaperpeer-review

125 Scopus citations


Current disk prefetch policies in major operating systems track access patterns at the level of the file abstraction. While this is useful for exploiting application-level access patterns, file-level prefetching cannot realize the full performance improvements achievable by prefetching. There are two reasons for this. First, certain prefetch opportunities can only be detected by knowing the data layout on disk, such as the contiguous layout of file metadata or data from multiple files. Second, non-sequential access of disk data (requiring disk head movement) is much slower than sequential access, and the penalty for mis-prefetching a 'random' block, relative to that of a sequential block, is correspondingly more costly. To overcome the inherent limitations of prefetching at the logical file level, we propose to perform prefetching directly at the level of disk layout, and in a portable way. Our technique, called DiskSeen, is intended to be supplementary to, and to work synergistically with, file-level prefetch policies, if present. DiskSeen tracks the locations and access times of disk blocks, and based on analysis of their temporal and spatial relationships, seeks to improve the sequentiality of disk accesses and overall prefetching performance. Our implementation of the DiskSeen scheme in the Linux 2.6 kernel shows that it can significantly improve the effectiveness of prefetching, reducing execution times by 20%-53% for micro-benchmarks and real applications such as grep, CVS, and TPC-H.

Original languageEnglish (US)
Number of pages14
StatePublished - 2007
Externally publishedYes
Event2007 USENIX Annual Technical Conference, USENIX 2007 - Santa Clara, United States
Duration: Jun 17 2007Jun 22 2007


Conference2007 USENIX Annual Technical Conference, USENIX 2007
Country/TerritoryUnited States
CitySanta Clara

All Science Journal Classification (ASJC) codes

  • General Computer Science


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