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Title: Optimal neural computations require analog processors

Abstract

This paper discusses some of the limitations of hardware implementations of neural networks. The authors start by presenting neural structures and their biological inspirations, while mentioning the simplifications leading to artificial neural networks. Further, the focus will be on hardware imposed constraints. They will present recent results for three different alternatives of parallel implementations of neural networks: digital circuits, threshold gate circuits, and analog circuits. The area and the delay will be related to the neurons` fan-in and to the precision of their synaptic weights. The main conclusion is that hardware-efficient solutions require analog computations, and suggests the following two alternatives: (i) cope with the limitations imposed by silicon, by speeding up the computation of the elementary silicon neurons; (2) investigate solutions which would allow the use of the third dimension (e.g. using optical interconnections).

Authors:
Publication Date:
Research Org.:
Los Alamos National Lab., Div. of Space and Atmospheric Sciences, NM (United States)
Sponsoring Org.:
USDOE Assistant Secretary for Human Resources and Administration, Washington, DC (United States)
OSTI Identifier:
334348
Report Number(s):
LA-UR-98-3325; CONF-9809118-
ON: DE99002277; TRN: AHC29914%%152
DOE Contract Number:  
W-7405-ENG-36
Resource Type:
Conference
Resource Relation:
Conference: Intenational conference on parallel computing in electrical engineering, Biialystok (Poland), 2-5 Sep 1998; Other Information: PBD: [1998]
Country of Publication:
United States
Language:
English
Subject:
99 MATHEMATICS, COMPUTERS, INFORMATION SCIENCE, MANAGEMENT, LAW, MISCELLANEOUS; NEURAL NETWORKS; OPTIMIZATION; ANALOG SYSTEMS; IMPLEMENTATION; DIGITAL CIRCUITS; GATING CIRCUITS

Citation Formats

Beiu, V. Optimal neural computations require analog processors. United States: N. p., 1998. Web.
Beiu, V. Optimal neural computations require analog processors. United States.
Beiu, V. 1998. "Optimal neural computations require analog processors". United States. https://www.osti.gov/servlets/purl/334348.
@article{osti_334348,
title = {Optimal neural computations require analog processors},
author = {Beiu, V},
abstractNote = {This paper discusses some of the limitations of hardware implementations of neural networks. The authors start by presenting neural structures and their biological inspirations, while mentioning the simplifications leading to artificial neural networks. Further, the focus will be on hardware imposed constraints. They will present recent results for three different alternatives of parallel implementations of neural networks: digital circuits, threshold gate circuits, and analog circuits. The area and the delay will be related to the neurons` fan-in and to the precision of their synaptic weights. The main conclusion is that hardware-efficient solutions require analog computations, and suggests the following two alternatives: (i) cope with the limitations imposed by silicon, by speeding up the computation of the elementary silicon neurons; (2) investigate solutions which would allow the use of the third dimension (e.g. using optical interconnections).},
doi = {},
url = {https://www.osti.gov/biblio/334348}, journal = {},
number = ,
volume = ,
place = {United States},
year = {1998},
month = {12}
}

Conference:
Other availability
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