DULO: an effective buffer cache management scheme to exploit both temporal and spatial locality

  • Authors:

  • Song Jiang;Xiaoning Ding;Feng Chen;Enhua Tan;Xiaodong Zhang

  • Affiliations:

  • Performance & Architecture Laboratory, Computer & Computational Sciences Div., Los Alamos National Laboratory, Los Alamos, NM;Department of Computer Science and Engineering, Ohio State University, Columbus, OH;Department of Computer Science and Engineering, Ohio State University, Columbus, OH;Department of Computer Science and Engineering, Ohio State University, Columbus, OH;Department of Computer Science and Engineering, Ohio State University, Columbus, OH

  • Venue:
  • FAST'05 Proceedings of the 4th conference on USENIX Conference on File and Storage Technologies - Volume 4
  • Year:
  • 2005

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Abstract

Sequentiality of requested blocks on disks, or their spatial locality, is critical to the performance of disks, where the throughput of accesses to sequentially placed disk blocks can be an order of magnitude higher than that of accesses to randomly placed blocks. Unfortunately, spatial locality of cached blocks is largely ignored and only temporal locality is considered in system buffer cache management. Thus, disk performance for workloads without dominant sequential accesses can be seriously degraded. To address this problem, we propose a scheme called DULO (DUal LOcality), which exploits both temporal and spatial locality in buffer cache management. Leveraging the filtering effect of the buffer cache, DULO can influence the I/O request stream by making the requests passed to disk more sequential, significantly increasing the effectiveness of I/O scheduling and prefetching for disk performance improvements. DULO has been extensively evaluated by both trace-driven simulations and a prototype implementation in Linux 2.6.11. In the simulations and system measurements, various application workloads have been tested, including Web Server, TPC benchmarks, and scientific programs. Our experiments show that DULO can significantly increase system throughput and reduce program execution times.