Paper Info
Title
Neural computing on a one dimensional SIMD array
Abstract
Parallel processors offer a very attractive mechanism for the implementation of large neural networks. Problems in the usage of parallel processing in neural computing involve the difficulty of handling the large amount of global communication between processing units and the storage of weights for each of the neural processor connections. This paper will discuss how massive parallelism in the form of a one dimensional SIMD array can handle indefinitely large networks in near real time by efficiently organizing the memory storage of weights, and input and output signals. Very little overhead time is used in communication of signals between processing units, and there is no idle time for any of the units. An advantage of SIMD array systems is that the arithmetic processing is done bit serially, with the result that trade-offs can be easily be made between the processor speed and precision of the signals and weights.
Year
Venue
Keywords
1989
IJCAI
arithmetic processing,dimensional simd array,near real time,neural processor connection,parallel processing,large amount,overhead time,neural computing,large neural network,idle time,large network,neural network
Field
DocType
Citations 
Large networks,Computer science,Massively parallel,Parallel processing,Parallel computing,Input/output,Simd array,Artificial intelligence,Artificial neural network,Clock rate,Machine learning,Idle time
Conference
3
PageRank 
References 
Authors
1.03
5
1
Name
Order
Citations
PageRank
Stephen S. Wilson11018.28