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Design method for Unconventional Computing

Spaanenburg, Lambert LU ; Åkesson, B; Hansson, A and Goossens, K (2006) 10th Int. Workshop on Cellular Neural Networks and their Applications (CNNA) In Proceedings 10th IEEE Workshop on CNNA and their Applications p.334-339
Abstract
Network-on-Chip concepts allow moving away from the classical, centralized computer. The meaningful collaboration of computing units over a well-behaved network creates the infinite state space that underlies the Turing computer concept. The combinatorial state explosion that results from a Network-on-Chip will easily prove more valuable than the mere technological progress in memory storage, when the network nodes become small enough. Embedded Super-Computing has this unconventional goal. This paper introduces a design method for such computing concepts. It discusses how a software simulation is gradually migrated into a Network-on-Chip implementation. The approach is illustrated by the development of a Cellular Neural Network as a... (More)
Network-on-Chip concepts allow moving away from the classical, centralized computer. The meaningful collaboration of computing units over a well-behaved network creates the infinite state space that underlies the Turing computer concept. The combinatorial state explosion that results from a Network-on-Chip will easily prove more valuable than the mere technological progress in memory storage, when the network nodes become small enough. Embedded Super-Computing has this unconventional goal. This paper introduces a design method for such computing concepts. It discusses how a software simulation is gradually migrated into a Network-on-Chip implementation. The approach is illustrated by the development of a Cellular Neural Network as a typical example of a well-behaved network on small, embedded nodes. (Less)
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
Cellular Neural Networks, Network-on-Chip, System-on-Silicon., Field programmable gate arrays
in
Proceedings 10th IEEE Workshop on CNNA and their Applications
pages
334 - 339
publisher
IEEE--Institute of Electrical and Electronics Engineers Inc.
conference name
10th Int. Workshop on Cellular Neural Networks and their Applications (CNNA)
external identifiers
  • WOS:000245392200071
  • Scopus:47549109241
ISBN
1-4244-0640-4
DOI
10.1109/CNNA.2006.341655
language
English
LU publication?
yes
id
22b6ee6c-a3ba-4981-b72a-5c92b05f4673 (old id 603757)
date added to LUP
2007-12-04 13:48:49
date last changed
2017-01-01 07:54:52
@inproceedings{22b6ee6c-a3ba-4981-b72a-5c92b05f4673,
  abstract     = {Network-on-Chip concepts allow moving away from the classical, centralized computer. The meaningful collaboration of computing units over a well-behaved network creates the infinite state space that underlies the Turing computer concept. The combinatorial state explosion that results from a Network-on-Chip will easily prove more valuable than the mere technological progress in memory storage, when the network nodes become small enough. Embedded Super-Computing has this unconventional goal. This paper introduces a design method for such computing concepts. It discusses how a software simulation is gradually migrated into a Network-on-Chip implementation. The approach is illustrated by the development of a Cellular Neural Network as a typical example of a well-behaved network on small, embedded nodes.},
  author       = {Spaanenburg, Lambert and Åkesson, B and Hansson, A and Goossens, K},
  booktitle    = {Proceedings 10th IEEE Workshop on CNNA and their Applications},
  isbn         = {1-4244-0640-4},
  keyword      = {Cellular Neural Networks,Network-on-Chip,System-on-Silicon.,Field programmable gate arrays},
  language     = {eng},
  pages        = {334--339},
  publisher    = {IEEE--Institute of Electrical and Electronics Engineers Inc.},
  title        = {Design method for Unconventional Computing},
  url          = {http://dx.doi.org/10.1109/CNNA.2006.341655},
  year         = {2006},
}