Title :
Implementation of a feed-forward Artificial Neural Network in VHDL on FPGA
Author :
Dondon, Philippe ; Carvalho, Julien ; Gardere, Remi ; Lahalle, Paul ; Tsenov, Georgi ; Mladenov, Valeri
Author_Institution :
ENSEIRB-MATMECA, Ecole Nat. Super. d´Electron., France
Abstract :
Describing an Artificial Neural Network (ANN) using VHDL allows a further implementation of such a system on FPGA. Indeed, the principal point of using FPGA for ANNs is flexibility that gives it an advantage toward other systems like ASICS which are entirely dedicated to one unique architecture and allowance to parallel programming, which is inherent to ANN calculation system and one of their advantages. Usually FPGAs do not have unlimited logical resources integrated in a single package and this limitation forcesrequirement for optimizations for the design in order to have the best efficiency in terms of speed and resource consumption. This paper deals with the VHDL designing problems which can be encountered when trying to describe and implement such ANNs on FPGAs.
Keywords :
feedforward neural nets; field programmable gate arrays; hardware description languages; parallel programming; ANN calculation system; ASICS; FPGA; VHDL designing problems; feedforward artificial neural network; logical resources; parallel programming; resource consumption; Artificial neural networks; Biological neural networks; Field programmable gate arrays; MATLAB; Neurons; Random access memory; Read only memory; FPGA implementation; VHDL; neural networks; nonlinear systems;
Conference_Titel :
Neural Network Applications in Electrical Engineering (NEUREL), 2014 12th Symposium on
Conference_Location :
Belgrade
Print_ISBN :
978-1-4799-5887-0
DOI :
10.1109/NEUREL.2014.7011454