DocumentCode
2286047
Title
Modeling neural networks on the MPP
Author
Hicklin, Joe ; Demuth, Howard
Author_Institution
Dept. of Electr. Eng., Idaho Univ., Moscow, ID, USA
fYear
1988
fDate
10-12 Oct 1988
Firstpage
39
Lastpage
42
Abstract
A network of fixed-connection-weight neuronlike elements is simulated on the massively parallel processor (MPP) in two ways. First, the square connectivity matrix of a 128-neuron network is mapped onto the square MPP processor array. This allows a highly parallel simulation in which 128 MPP processors were active at all times. Second, a 128-by-128 array of neurons is mapped onto the 16.384 MPP processors. Here the MPP processor limits neuron connections somewhat, but all MPP processors are active at all times and a large speedup is obtained. The first simulation, based on mathematics (weight matrix), produces a significant speedup but tends to obscure the second faster simulation based on mapping the physics (entire physical description) of the neural network onto the MPP. The authors suggest that alternative mappings onto the MPP should be sought and examined carefully
Keywords
digital simulation; neural nets; parallel processing; highly parallel simulation; massively parallel processor; mathematics; square connectivity matrix; weight matrix; Fires; Mathematics; Nearest neighbor searches; Network topology; Neural networks; Neurons; Physics;
fLanguage
English
Publisher
ieee
Conference_Titel
Frontiers of Massively Parallel Computation, 1988. Proceedings., 2nd Symposium on the Frontiers of
Conference_Location
Fairfax, VA
Print_ISBN
0-8186-5892-4
Type
conf
DOI
10.1109/FMPC.1988.47410
Filename
47410
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