TY - GEN
T1 - Optimal mapping of neural networks onto FPGAs1 - A new constructive algorithm
AU - Beiu, Valeriu
AU - Taylor, John G.
N1 - Publisher Copyright:
© 1995, Springer Verlag. All rights reserved.
PY - 1995
Y1 - 1995
N2 - The paper shows how a feedforward neural network defined by a set of m binary examples of n bits each, can be determined by a novel constructive algorithm (which determines the number of layers, the number of neurons in each layer and the synaptic weights of a particular neural network). For doing that, the optimisation criteria of the new algorithm can be chosen from the following: (i) the area of the circuit A; (ii) the AT2 complexity measure of VLSI; (iii) the delay T; or (iv) the maximum fan-in for a gate A. As a result the neural network which is build can be optimised for mapping onto a FPGA. By considering the maximum fan-in of one neuron as a parameter, we proceed to show its influence on the area, and suggest how to obtain a full class of solutions. We also compare our results with other constructive algorithms and benchmark it on the classical “two spirals problem.” Conclusions and some open problems are closing the paper.
AB - The paper shows how a feedforward neural network defined by a set of m binary examples of n bits each, can be determined by a novel constructive algorithm (which determines the number of layers, the number of neurons in each layer and the synaptic weights of a particular neural network). For doing that, the optimisation criteria of the new algorithm can be chosen from the following: (i) the area of the circuit A; (ii) the AT2 complexity measure of VLSI; (iii) the delay T; or (iv) the maximum fan-in for a gate A. As a result the neural network which is build can be optimised for mapping onto a FPGA. By considering the maximum fan-in of one neuron as a parameter, we proceed to show its influence on the area, and suggest how to obtain a full class of solutions. We also compare our results with other constructive algorithms and benchmark it on the classical “two spirals problem.” Conclusions and some open problems are closing the paper.
UR - http://www.scopus.com/inward/record.url?scp=0344828787&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=0344828787&partnerID=8YFLogxK
U2 - 10.1007/3-540-59497-3_256
DO - 10.1007/3-540-59497-3_256
M3 - Conference contribution
AN - SCOPUS:0344828787
SN - 3540594973
SN - 9783540594970
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 822
EP - 829
BT - From Natural to Artificial Neural Computation - International Workshop on Artificial Neural Networks, Proceedings
A2 - Mira, Jose
A2 - Sandoval, Francisco
PB - Springer Verlag
T2 - 3rd International Workshop on Artificial Neural Networks, IWANN 1995
Y2 - 7 June 1995 through 9 June 1995
ER -