@InProceedings{madhyastha:global,
  author = {Tara M. Madhyastha and Daniel A. Reed},
  title = {Exploiting Global Input/Output Access Pattern Classification},
  booktitle = {Proceedings of SC97: High Performance Networking and Computing},
  year = {1997},
  month = {November},
  publisher = {ACM Press},
  address = {San Jose},
  later = {madhyastha:thesis},
  URL = {http://www.supercomp.org/sc97/proceedings/TECH/MADHYAST/INDEX.HTM},
  keywords = {file access pattern, parallel I/O, pario-bib},
  abstract = {Parallel input/output systems attempt to alleviate the
  performance bottleneck that affects many input/output intensive applications.
  In such systems, an understanding of the application access pattern,
  especially how requests from multiple processors for different file regions
  are logically related, is important for optimizing file system performance.
  We propose a method for automatically classifying these global access
  patterns and using these global classifications to select and tune file
  system policies to improve input/output performance. We demonstrate this
  approach on benchmarks and scientific applications using global
  classification to automatically select appropriate underlying Intel PFS
  input/output modes and server buffering strategies.},
  comment = {No page numbers: web and CDROM proceedings only. See also
  madhyastha:thesis and related papers.}
}