A high-performance distributed parallel file system for data-intensive computations

Xiaohui Shen*, Alok Choudhary

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

One of the challenges brought by large-scale scientific applications is how to avoid remote storage access by collectively using sufficient local storage resources to hold huge amounts of data generated by the simulation while providing high-performance I/O. DPFS, a distributed parallel file system, is designed and implemented to address this problem. DPFS collects locally distributed and unused storage resources as a supplement to the internal storage of parallel computing systems to satisfy the storage capacity requirement of large-scale applications. In addition, like parallel file systems, DPFS provides striping mechanisms that divide a file into small pieces and distributes them across multiple storage devices for parallel data access. The unique feature of DPFS is that it provides three file levels with each file level corresponding to a file striping method. In addition to the traditional linear striping method, DPFS also provides a novel Multidimensional striping method that can solve performance problems of linear striping for many popular access patterns. Other issues such as load-balancing and user interface are also addressed in DPFS.

Original languageEnglish (US)
Pages (from-to)1157-1167
Number of pages11
JournalJournal of Parallel and Distributed Computing
Volume64
Issue number10
DOIs
StatePublished - Oct 2004

Funding

This research was in part supported by Department of Energy under the Accelerated Strategic Computing Initiative (ASCI) Academic Strategic Alliance Program (ASAP) Level 2, under subcontract No W-7405-ENG-48 from Lawrence Livermore National Laboratories. We also thank Prof. Baner-jee and Prof. Taylor of ECE department at Northwestern University for allowing us to use their students’ workstations to run our DPFS servers.

Keywords

  • Data intensive applications
  • Distributed file system
  • I/O
  • Parallel file system
  • Striping

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Hardware and Architecture
  • Computer Networks and Communications
  • Artificial Intelligence

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