Artificial neural networks: a review of commercial hardware

Artificial Neural Networks became a common solution for a wide variety of problems in many fields, such as control and pattern recognition to name but a few. Many solutions found in these and other Artificial Neural Network fields have reached a hardware implementation phase, either commercial or with prototypes. The most frequent solution for the implementation of Artificial Neural Networks consists of training and implementing the Artificial Neural Networks within a computer. Nevertheless this solution might be unsuitable because of its cost or its limited speed. The implementation might be too expensive because of the computer and too slow when implemented in software. In both cases dedicated hardware can be an interesting solution. The necessity of dedicated hardware might not imply building the hardware since in the last two decades several commercial hardware solutions that can be used in the implementation have reached the market. Unfortunately not every integrated circuit will fit the needs: some will use lower precision, some will implement only certain types of networks, some don’t have training built in and the information is not easy to find. This article is confined to reporting the commercial chips that have been developed specifically for Artificial Neural Networks, leaving out others solutions. This option has been made because most of the other solutions are based on cards which are built either with these chips, Digital Signal Processors or Reduced Instruction Set Computers. © 2003 Elsevier Science Lta. All rights reserved.