An efficient collective communication method for Grid scale networks

Kyung Lang Park, Hwang Jik Lee, Youn Joo Lee, Oh Young Kwon, Sung Yong Park, Hyung Woo Park, Shin Dug Kim

Research output: Chapter in Book/Report/Conference proceedingChapter

6 Citations (Scopus)

Abstract

This research is to design a collection of effective collective operations for the Grid scale network environment. In the Grid, several network features should be specified and adapted into the algorithmic design of collective operations. For this, we characterize the Grid and design hierarchical latency optimal tree algorithm for the MPI (message passing interface) library. The experimental results show that performance gain in performing collective operations can be achieved by around 160% compared with MPICH-G2 which is based on the flat algorithm.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsPeter M. A. Sloot, David Abramson, Alexander V. Bogdanov, Yuriy E. Gorbachev, Jack J. Dongarra, Albert Y. Zomaya
PublisherSpringer Verlag
Pages819-828
Number of pages10
ISBN (Print)3540401970, 9783540401971
DOIs
Publication statusPublished - 2003

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2660
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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    Park, K. L., Lee, H. J., Lee, Y. J., Kwon, O. Y., Park, S. Y., Park, H. W., & Kim, S. D. (2003). An efficient collective communication method for Grid scale networks. In P. M. A. Sloot, D. Abramson, A. V. Bogdanov, Y. E. Gorbachev, J. J. Dongarra, & A. Y. Zomaya (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 819-828). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2660). Springer Verlag. https://doi.org/10.1007/3-540-44864-0_84