Poster: A scalable two-phase parallel I/O library with application to a large scale subsurface simulator

Sarat Sreepathi, Vamsi Sripathi, Glenn Hammond, Richard Mills, G. Kumar Mahinthakumar

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This poster describes the development of a highly scalable application layer parallel I/O library (ASCEM-IO) for sci-entific applications.This library was envisioned to leverage our earlier I/O optimization experience to build a scalable general purpose parallel I/O capability for any application. The parallel I/O library provides a higher level API (Ap-plication Programming Interface) to read and write large scientific datasets in parallel at very large processor counts. Specifically, the goal is to take advantage of existing parallel I/O libraries, such as HDF5 which are being widely used by scientific applications and modify these algorithms to better scale on larger number of processors. This is accomplished by dividing the traditional I/O operations (read/write) into two phases, a communication phase and an I/O phase. Re-sults with a real application on the Cray XT/5 indicates sig-nificant performance improvement on large processor cores when compared to default HDF collective I/O operations.

Original languageEnglish
Title of host publicationSC'11 - Proceedings of the 2011 High Performance Computing Networking, Storage and Analysis Companion, Co-located with SC'11
Pages67-68
Number of pages2
DOIs
StatePublished - 2011
Externally publishedYes
Event2011 High Performance Computing Networking, Storage and Analysis, SC'11, Co-located with SC'11 - Seattle, WA, United States
Duration: Nov 12 2011Nov 18 2011

Publication series

NameSC'11 - Proceedings of the 2011 High Performance Computing Networking, Storage and Analysis Companion, Co-located with SC'11

Conference

Conference2011 High Performance Computing Networking, Storage and Analysis, SC'11, Co-located with SC'11
Country/TerritoryUnited States
CitySeattle, WA
Period11/12/1111/18/11

Keywords

  • High Performance Computing
  • Parallel I/O

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