GPAW optimized for Blue Gene/P using hybrid programming

Mads Ruben Burgdorff Kristensen, Hans Henrik Happe, Brian Vinter

5 Citations (Scopus)
2746 Downloads (Pure)

Abstract

In this work we present optimizations of a Grid-based projector-augmented wave method software, GPAW for the Blue Gene/P architecture. The improvements are achieved by exploring the advantage of shared and distributed memory programming also known as hybrid programming. The work focuses on optimizing a very time consuming operation in GPAW, the finite-different stencil operation, and different hybrid programming approaches are evaluated. The work succeeds in demonstrating a hybrid programming model which is clearly beneficial compared to the original flat programming model. In total an improvement of 1.94 compared to the original implementation is obtained. The results we demonstrate here are reasonably general and may be applied to other finite difference codes.
Original languageEnglish
Title of host publicationProceedings of the 2009 IEEE International Symposium on Parallel & Distributed Processing
Number of pages6
PublisherIEEE
Publication date2009
Pages1-6
ISBN (Electronic)978-1-4244-3751-1
DOIs
Publication statusPublished - 2009
EventInternational Parallel and Distributed Processing Symposium (IPDPS 2009) - Rom, Italy
Duration: 23 May 200929 May 2009
Conference number: 23

Conference

ConferenceInternational Parallel and Distributed Processing Symposium (IPDPS 2009)
Number23
Country/TerritoryItaly
CityRom
Period23/05/200929/05/2009

Keywords

  • Faculty of Science
  • HPC
  • Hybrid parallel programming
  • Parallel framework
  • GPAW

Fingerprint

Dive into the research topics of 'GPAW optimized for Blue Gene/P using hybrid programming'. Together they form a unique fingerprint.

Cite this