Title :
Artificial neural networks implementation on vectorial supercomputers
Author :
Sánchez, E. ; Barro, S. ; Regueiro, C.V.
Author_Institution :
Departamento de Electron. y Computacion, Santiago de Compostela Univ., Spain
fDate :
27 Jun- 2 Jul 1994
Abstract :
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
Keywords :
backpropagation; multilayer perceptrons; multiprocessing systems; parallel machines; vector processor systems; virtual machines; FUJITSU VP-2400/10 vectorial supercomputer; artificial neural networks; backpropagation algorithm; compiler directives; conditional statement treatment; do-loops vectorization; input/output structures; maximum performance; multilayer perceptron; structural complexity; Artificial neural networks; Backpropagation algorithms; Computer networks; Equations; Multilayer perceptrons; Neurons; Nonhomogeneous media; Speech recognition; Supercomputers; Very large scale integration;
Conference_Titel :
Neural Networks, 1994. IEEE World Congress on Computational Intelligence., 1994 IEEE International Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-1901-X
DOI :
10.1109/ICNN.1994.374841
