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Data Distribution Concepts for Parallel Image Processing \Lambda Michael N olle and Gerald Schreiber

Summary: Data Distribution Concepts for Parallel Image Processing \Lambda
Michael N˜ olle and Gerald Schreiber
Technische Informatik I, University of Technology Hamburg--Harburg
21071 Hamburg, Germany
email: fnoelle, g­schreiberg@tu­harburg.d400.de
Proceedings of the 13th Internationall Conference on Pattern Recognition
(ICPR'96), August 25­30, 1996 Technical University of Vienna, Austria
Data distributions gained a considerable interest in the
field of data parallel programming. In most cases they
are key factors for the efficiency of the implementation. In
this paper we analyze data distributions suited for parallel
image processing and those defined by some of todays more
popular parallel languages (HPF, Vienna Fortran, pC++)
and libraries (ScaLAPACK). The majority of them belong
to the class of bit permutations. These permutations can
efficiently be realized on networks that are based on shuffle
permutations. As a result we propose to widen the scope
of data distributions tolerated by parallel languages and
libraries towards classes of distributions. For the large


Source: Albert-Ludwigs-Universität Freiburg, Institut für Informatik,, Lehrstuhls für Mustererkennung und Bildverarbeitung


Collections: Computer Technologies and Information Sciences