Exploiting Shape in Parallel Programming (1996)
| Citations: | 5 - 2 self |
BibTeX
@MISC{Jay96exploitingshape,
author = {C. Barry Jay and C. Barry and Jay David and David G. Clarke and Jenny J. Edwards},
title = {Exploiting Shape in Parallel Programming},
year = {1996}
}
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Abstract
Shape theory is a new approach to data types and programming based on the separation of a data type into its "shape" and "data" parts. Shape is common in parallel computing. This paper identifies areas where the explicit use of shape reduces the burden of programming a parallel computer, via the implementation of Cholesky decomposition. keywords: shape, parallel programming, error detection, Cholesky decomposition Abstract Shape theory is a new approach to data types and programming based on the separation of a data type into its "shape" and "data" parts. Shape is common in parallel computing. This paper identifies areas where the explicit use of shape reduces the burden of programming a parallel computer, via the implementation of Cholesky decomposition. 1
Citations
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| 1 | Parallel Cholesky Factorisation - Edwards, Tomlin - 1992 |
| 1 | Chih Chung Huang, and Jun-Min Liu. Parallel Algorithms for - Housos - 1989 |
| 1 | Data categories. Computing: The Australian Theory Seminar - Jay - 1996 |
