DocumentCode :
3236825
Title :
ANN parallelization on a token-based simulated parallel system
Author :
Cristea, Alexandra Ioana ; Okamoto, Tatsuaki
Author_Institution :
Graduate Sch. of Inf. Syst., Univ. of Electro-Commun., Japan
fYear :
1999
fDate :
1999
Firstpage :
24
Lastpage :
28
Abstract :
We believe that parallelism is strongly connected with artificial neural networks (ANN), as biological neural networks are known to make good use of massive parallelism. At present, there has been little research in this direction. We have designed and implemented parallel ANNs on different environments. The best implementation possibilities are given, naturally, by massively parallel computers (dedicated or not). Still, even in the UNIX environment, which is based on the token-passing type of simulated parallelism, speed-ups are possible. In this paper, we demonstrate this statement on a very simple example problem, designed to perform a similar task to that of a feedforward ANN
Keywords :
Unix; feedforward neural nets; parallel processing; protocols; virtual machines; UNIX environment; artificial neural networks; feedforward neural net; implementation; massive parallelism; massively parallel computers; parallelization; speedup; token passing; token-based simulated parallel system; Algorithm design and analysis; Artificial neural networks; Biological neural networks; Biological system modeling; Broadcasting; Electronic mail; Hardware; Master-slave; Neurons; Parallel processing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence and Multimedia Applications, 1999. ICCIMA '99. Proceedings. Third International Conference on
Conference_Location :
New Delhi
Print_ISBN :
0-7695-0300-4
Type :
conf
DOI :
10.1109/ICCIMA.1999.798495
Filename :
798495
Link To Document :
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