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.
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NASA’s Thunderhead Cluster webpage, http://thunderhead.gsfc.nasa.gov/
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Valencia, D., Plaza, A., Rychkov, V., Lastovetsky, A. (2008). Efficient Collective Communication Paradigms for Hyperspectral Imaging Algorithms Using HeteroMPI. In: Lastovetsky, A., Kechadi, T., Dongarra, J. (eds) Recent Advances in Parallel Virtual Machine and Message Passing Interface. EuroPVM/MPI 2008. Lecture Notes in Computer Science, vol 5205. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87475-1_47
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DOI: https://doi.org/10.1007/978-3-540-87475-1_47
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-87474-4
Online ISBN: 978-3-540-87475-1
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