Performance-based parallel loop self-scheduling on heterogeneous multicore PC clusters

Chao Tung Yang, Jen Hsiang Chang, Chao-Chin Wu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In recent years, Multicore computers have been widely included in cluster systems. They adopt shared memory architectures. However, previous researches on parallel loop self-scheduling did not consider the feature of multicore computers. It is more suitable for shared-memory multiprocessors to adopt OpenMP for parallel programming. In this paper, we propose a performance-based approach that partitions loop iterations according to the performance weighting of cluster nodes. Because the iterations assigned to one MPI process will be processed in parallel by OpenMP threads running by the processor cores in the same computational node, the number of loop iterations to be allocated to one computational node at each scheduling step also depends on the number of processor cores in that node. Experimental results show that the proposed approach performs better than previous schemes.

Original languageEnglish
Title of host publicationHigh Performance Computing and Applications - Second International Conference, HPCA 2009, Revised Selected Papers
Pages509-514
Number of pages6
DOIs
Publication statusPublished - 2010 May 3
Event2nd International Conference on High-Performance Computing and Applications, HPCA 2009 - Shanghai, China
Duration: 2009 Aug 102009 Aug 12

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5938 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other2nd International Conference on High-Performance Computing and Applications, HPCA 2009
CountryChina
CityShanghai
Period09-08-1009-08-12

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Fingerprint Dive into the research topics of 'Performance-based parallel loop self-scheduling on heterogeneous multicore PC clusters'. Together they form a unique fingerprint.

  • Cite this

    Yang, C. T., Chang, J. H., & Wu, C-C. (2010). Performance-based parallel loop self-scheduling on heterogeneous multicore PC clusters. In High Performance Computing and Applications - Second International Conference, HPCA 2009, Revised Selected Papers (pp. 509-514). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5938 LNCS). https://doi.org/10.1007/978-3-642-11842-5_71