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H. Li, M. Maresca, "PolymorphicTorus Architecture for Computer Vision," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 11, no. 3, pp. 233243, March, 1989.  
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@article{ 10.1109/34.21792, author = {H. Li and M. Maresca}, title = {PolymorphicTorus Architecture for Computer Vision}, journal ={IEEE Transactions on Pattern Analysis and Machine Intelligence}, volume = {11}, number = {3}, issn = {01628828}, year = {1989}, pages = {233243}, doi = {http://doi.ieeecomputersociety.org/10.1109/34.21792}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }  
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TY  JOUR JO  IEEE Transactions on Pattern Analysis and Machine Intelligence TI  PolymorphicTorus Architecture for Computer Vision IS  3 SN  01628828 SP233 EP243 EPD  233243 A1  H. Li, A1  M. Maresca, PY  1989 KW  parallel architectures; dynamically reconfigurable network; computer vision; SIMD; machine vision; polymorphictorus network; circuit switching; mesh; tree; pyramid; hypercube; VLSI efficiency; computer vision; parallel algorithms; parallel architectures; VLSI VL  11 JA  IEEE Transactions on Pattern Analysis and Machine Intelligence ER   
A massively parallel finegrained SIMD (singleinstruction multidatastream) computer for machine vision computations is described. The architecture features a polymorphictorus network which inserts an individually controllable switch into every node of the twodimensional torus such that the network is dynamically reconfigurable to match the algorithm. Reconfiguration is accomplished by circuit switching and is achieved at finegrained level. Using both the processor coordinate in the torus and the data for reconfiguration, the polymorphictorus achieves solution time that is superior or equivalent to that of popular vision architectures such as mesh, tree, pyramid and hypercube for many vision algorithms discussed. Implementation of the architecture is given to illustrate its VLSI efficiency.
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