A High-Speed Analog Neural Processor

Authors:
Peter Masa;Klaas Hoen;Hans Wallinga
Affiliations:
Univ. of Twente, The Netherlands;Univ. of Twente, The Netherlands;Univ. of Twente, The Netherlands
Venue:
IEEE Micro
Year:
1994

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Abstract

Targeted at high-energy physics research applications, our special-purpose analog neural processor can classify up to 70 dimensional vectors within 50 nanoseconds. The decision-making process of the implemented feedforward neural network enables this type of computation to tolerate weight discretization, synapse nonlinearity, noise, and other non-ideal effects. Although our prototype does not take advantage of advanced CMOS technology, and was fabricated using a 2.5-/spl mu/m CMOS process, it performs 6 billion multiplications per second, with only 2 W dissipation, and has as high as 1.5 Gbyte/s equivalent bandwidth.