Efficient Collective Communication Paradigms for Hyperspectral Imaging Algorithms Using HeteroMPI

Authors:
David Valencia;Antonio Plaza;Vladimir Rychkov;Alexey Lastovetsky
Affiliations:
Technology of Computers and Communications Dept.,Technical School of Cáceres, University of Extremadura, Cáceres, Spain E-10071;Technology of Computers and Communications Dept.,Technical School of Cáceres, University of Extremadura, Cáceres, Spain E-10071;Heterogeneous Computing Laboratory, School of Computer Science and Informatics, University College Dublin, Belfield, Dublin 4, Ireland;Heterogeneous Computing Laboratory, School of Computer Science and Informatics, University College Dublin, Belfield, Dublin 4, Ireland
Venue:
Proceedings of the 15th European PVM/MPI Users' Group Meeting on Recent Advances in Parallel Virtual Machine and Message Passing Interface
Year:
2008

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Abstract

Most of the parallel strategies used for information extraction in remotely sensed hyperspectral imaging applications have been implemented in the form of parallel algorithms on both homogeneous and heterogeneous networks of computers. In this paper, we develop a study on efficient collective communications based on the usage of HeteroMPI for a parallel heterogeneous hyperspectral imaging algorithm which uses concepts of mathematical morphology.