Conference proceeding
A methodology for generating data distributions to optimize communication
Proceedings of the Fourth IEEE Symposium on Parallel and Distributed Processing, pp 436-441
1992
Abstract
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.< >
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5 citations in Scopus
Details
- Title
- A methodology for generating data distributions to optimize communication
- Creators
- S.K.S Gupta - The Ohio State UniversityS.D Kaushik - The Ohio State UniversityC.-H Huang - The Ohio State UniversityJ.R JohnsonR.W JohnsonP Sadayappan
- Publication Details
- Proceedings of the Fourth IEEE Symposium on Parallel and Distributed Processing, pp 436-441
- Conference
- 4th IEEE Symposium on Parallel and Distributed Processing, 4th
- Publisher
- IEEE
- Number of pages
- 1
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Computer Science
- Scopus ID
- 2-s2.0-84976839993
- Other Identifier
- 991019173809504721