GPU powered CNN simulator (SIMCNN) with graphical flow based programmability

In this paper, we introduce an innovative CNN algorithm development environment that significantly assists algorithmic design. The introduced graphical user interface uses Matlab Simulink with UMF-like program description, where direct functionality accompanies better accessability. The new generati...

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Bibliographic Details
Published in2008 11th International Workshop on Cellular Neural Networks and Their Applications pp. 163 - 168
Main Authors Soos, B.G., Rak, A., Veres, J., Cserey, G.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.07.2008
Subjects
Algorithm design and analysis
Computational modeling
Computer architecture
Computers
Hardware
Pixel
Program processors
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ISBN142442089X
9781424420896
ISSN2165-0144
DOI10.1109/CNNA.2008.4588671

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Summary:In this paper, we introduce an innovative CNN algorithm development environment that significantly assists algorithmic design. The introduced graphical user interface uses Matlab Simulink with UMF-like program description, where direct functionality accompanies better accessability. The new generation of graphical cards incorporate many general purpose graphics processing units, giving the power of parallel computing to a simple PC environment cheaply. Therefore, analysis of CNN dynamics become more feasible with a common hardware setup. Our measurements demonstrate the efficiency of the realized system. In the case of simpler algorithms, real-time execution is also possible.
ISBN:142442089X
9781424420896
ISSN:2165-0144
DOI:10.1109/CNNA.2008.4588671