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. © 2008 Springer-Verlag Berlin Heidelberg.
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Valencia, D., Plaza, A., Rychkov, V., & Lastovetsky, A. (2008). Efficient collective communication paradigms for hyperspectral imaging algorithms using HeteroMPI. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5205 LNCS, pp. 326–331). https://doi.org/10.1007/978-3-540-87475-1_47
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