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A methodology for generating data distributions to optimize communication

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6 Author(s)
Gupta, S.K.S. ; Dept. of Comput. & Inf. Sci., Ohio State Univ., Columbus, OH, USA ; Kaushik, S.D. ; Huang, C.-H. ; Johnson, J.R.
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The authors present an algebraic theory, based on the tensor product for describing the semantics of regular data distributions such as block, cyclic, and block-cyclic distributions. These distributions have been proposed in high performance Fortran, an ongoing effort for developing a Fortran extension for massively parallel computing. This algebraic theory has been used for designing and implementing block recursive algorithms on shared-memory and vector multiprocessors. In the present work, the authors extend this theory to generate programs with explicit data distribution commands from tensor product formulas. A methodology to generate data distributions that optimize communication is described. This methodology is demonstrated by generating efficient programs with data distribution for the fast Fourier transform

Published in:

Parallel and Distributed Processing, 1992. Proceedings of the Fourth IEEE Symposium on

Date of Conference:

1-4 Dec 1992