Evaluating structured I/O methods for parallel file systems

Avery Ching, Alok Choudhary, Wei Keng Liao, Robert Ross, William Gropp

Research output: Contribution to journalArticlepeer-review

Abstract

Modern data-intensive structured datasets constantly undergo manipulation and migration through parallel scientific applications. Directly supporting these time-consuming operations is an important step in providing high-performance I/O solutions for modern large-scale applications. High-level interfaces such as HDF5 and parallel netCDF provide convenient APIs for accessing structured datasets, and the MPI–IO interface also supports efficient access to structured data. Parallel file systems do not traditionally support such structured access from these higher level interfaces. In this work, we present two contributions. First, we demonstrate an implementation of structured data access support in the context of the Parallel Virtual File System (PVFS). We call this support ‘datatype I/O’ because of its similarity to MPI datatypes. This support is built with a reusable datatype-processing component from the MPICH2 MPI implementation. The second contribution of this work is a comparison of I/O characteristics of modern high-performance noncontiguous I/O methods. We use our I/O characteristics comparison to assess all the methods using three test applications. We also point to further optimisations that could be leveraged for even more efficient operation.

Original languageEnglish (US)
Pages (from-to)133-145
Number of pages13
JournalInternational Journal of High Performance Computing and Networking
Volume2
Issue number2-4
DOIs
StatePublished - 2004
Externally publishedYes

Keywords

  • MPI-IO
  • PVFS
  • datatype
  • evaluation
  • high performance
  • list I/O
  • noncontiguous
  • parallel I/O

ASJC Scopus subject areas

  • Software
  • Hardware and Architecture
  • Computer Networks and Communications

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