DocumentCode :
2371116
Title :
Switching networks and neural algorithms for reconstructing mesh-connected processor arrays with spares on their sides
Author :
Takanami, Itsuo ; Hisanaga, Yutaka ; Inoue, Katushi
Author_Institution :
Dept. of Inf. Eng., Iwate Univ., Morioka, Japan
fYear :
1994
fDate :
15-17 Nov 1994
Firstpage :
360
Lastpage :
365
Abstract :
First, we present switching networks and a reconstruction strategy for mesh-connected processor arrays with linear arrays of spares on their left/right/upper/bottom sides. Each faulty processor is compensated by a spare on any one of left/right/upper/bottom sides. The reconstruction is done by shifting vertically first and then horizontally. Such a new reconstruction strategy leads to the simple and systematic switching operations for the networks. The networks are regular and comparatively simple. The distances between logically adjacent processors after the reconstruction are bounded by a constant. Next, we describe exhaustive algorithms for reconstruction. It seems that efficient ones can not be found. So, using a Hopfield-type neural network model, we present algorithms for the two cases where the linear arrays of spares are on the right and bottom sides, and on the right and left and bottom sides, and show their effectiveness by computer simulation
Keywords :
Hopfield neural nets; digital simulation; multiprocessor interconnection networks; neural net architecture; redundancy; Hopfield-type neural network model; VLSI; computer simulation; exhaustive algorithms; linear arrays; logically adjacent processors; mesh-connected processor arrays; neural algorithms; reconstruction; reconstruction strategy; switching networks; switching operations; Computer network reliability; Computer networks; Computer simulation; Hopfield neural networks; Neural networks; Proposals; Very large scale integration; Wafer scale integration;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Test Symposium, 1994., Proceedings of the Third Asian
Conference_Location :
Nara
Print_ISBN :
0-8186-6690-0
Type :
conf
DOI :
10.1109/ATS.1994.367205
Filename :
367205
Link To Document :
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