DocumentCode
1838725
Title
State-flow and state-scan CNN architectures
Author
Spaanenburg, L. ; Malki, S.
Author_Institution
Dept. of Electr. & Inf. Technol., Lund Univ., Lund, Sweden
fYear
2010
fDate
3-5 Feb. 2010
Firstpage
1
Lastpage
6
Abstract
The Cellular Neural Network is an obvious candidate for multi-core realization. For reason of its seemingly simple architecture, it is therefore the ideal candidate to evaluate techniques for multi-core technology mapping. In this paper it is studied how a CNN implementation can be unrolled in space or in time to fit the specific characteristics of a multi-core platform. It illustrates that this is a crucial step that sets the basic performance of a multi-core realization.
Keywords
cellular neural nets; neural net architecture; CNN architectures; cellular neural network; multicore technology mapping; state flow; state scan; Cellular networks; Cellular neural networks; Computer networks; Distributed computing; Image processing; Information technology; Network-on-a-chip; Nonlinear equations; Processor scheduling; Space technology; Cellular Neural Networks; Dataflow Scheduling; Multi Core; Spatial Distribution; Time Multiplexing;
fLanguage
English
Publisher
ieee
Conference_Titel
Cellular Nanoscale Networks and Their Applications (CNNA), 2010 12th International Workshop on
Conference_Location
Berkeley, CA
Print_ISBN
978-1-4244-6679-5
Type
conf
DOI
10.1109/CNNA.2010.5430342
Filename
5430342
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