Optimizing noncontiguous accesses in MPI-IO

Rajeev Thakur, William Gropp, Ewing Lusk

Research output: Contribution to journalArticlepeer-review

Abstract

The I/O access patterns of many parallel applications consist of accesses to a large number of small, noncontiguous pieces of data. If an application's I/O needs are met by making many small, distinct I/O requests, however, the I/O performance degrades drastically. To avoid this problem, MPI-IO allows users to access noncontiguous data with a single I/O function call, unlike in Unix I/O. In this paper, we explain how critical this feature of MPI-IO is for high performance and how it enables implementations to perform optimizations. We first provide a classification of the different ways of expressing an application's I/O needs in MPI-IO - we classify them into four levels, called levels 0-3. We demonstrate that, for applications with noncontiguous access patterns, the I/O performance improves dramatically if users write their applications to make level-3 requests (noncontiguous, collective) rather than level-0 requests (Unix style). We then describe how our MPI-IO implementation, ROMIO, delivers high performance for noncontiguous requests. We explain in detail the two key optimizations ROMIO performs: data sieving for noncontiguous requests from one process and collective I/O for noncontiguous requests from multiple processes. We describe how we have implemented these optimizations portably on multiple machines and file systems, controlled their memory requirements, and also achieved high performance. We demonstrate the performance and portability with performance results for three applications - an astrophysics-application template (DIST3D), the NAS BTIO benchmark, and an unstructured code (UNSTRUC) - on five different parallel machines: HP Exemplar, IBM SP, Intel Paragon, NEC SX-4, and SGI Origin2000.

Original languageEnglish (US)
Pages (from-to)83-105
Number of pages23
JournalParallel Computing
Volume28
Issue number1
DOIs
StatePublished - Jan 2002
Externally publishedYes

Keywords

  • Collective I/O
  • Data sieving
  • MPI-IO
  • Parallel I/O

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Hardware and Architecture
  • Computer Networks and Communications
  • Computer Graphics and Computer-Aided Design
  • Artificial Intelligence

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