Switching networks and neural algorithms for reconstructing mesh-connected processor arrays with spares on their sides

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