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Artificial neural networks implementation on vectorial supercomputers

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3 Author(s)
E. Sanchez ; Departamento de Electron. y Computacion, Santiago de Compostela Univ., Spain ; S. Barro ; C. V. Regueiro

We present the results from the implementation of a multilayer perceptron with the backpropagation algorithm on a FUJITSU VP-2400/10 vectorial supercomputer. The programming methodology employed, tries to obtain the maximum performance in this kind of machines based on: input/output structures, treatment of conditional statements, do-loops vectorization and compiler directives. In this work, computing times for the VU (vectorial unit) and CPU are presented. These times indicate the possibility of real time operation in applications which demand artificial neural networks with a high structural complexity

Published in:

Neural Networks, 1994. IEEE World Congress on Computational Intelligence., 1994 IEEE International Conference on  (Volume:6 )

Date of Conference:

27 Jun- 2 Jul 1994