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Evolvable hardware chips for industrial applications

Authors:

Tetsuya Higuchi,

Nobuki KajiharaAuthors Info & Claims

Communications of the ACM, Volume 42, Issue 4

Pages 60 - 66

https://doi.org/10.1145/299157.299172

Published: 01 April 1999 Publication History

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References

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Goldberg, D.E. Genetic Algorithms in Search, Optimization, andMachine Learning. Addison-Wesley, 1989.

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Higuchi, T., Iwata, M., and Liu, W. Eds. In Proceedings of?irst International ConJ~rence on Evolvable Systems, Lecture Notes on Computer Science, 1259, Springer Verlag, 1996.

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[3]

Kajitani, I., Hoshino, T., Nishikawa, D., Yokoi, H., Nakaya, S., Yamauchi, T., Inuo, T., Kajihara, N., Iwata, M., Keymeulen, D., and Higuchi, T. A gate-level EHW chip: Implementing GA operations and reconfigurable hardware on a single LSI. In Proceedings of the International ConJ~rence on Evolvable Systems, (Sept. 1998), 1-12.

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Keymeulen, D., Iwata, M., Kuniyoshi, Y. and Higuchi, T. Comparison between an off-line model-free and an on-line model-based evolution applied to a robotics navigation system using evolvable hardware. In Artificial LiJ~ VI: Proceedings of the Sixth International ConJ~rence on Artificial Li~, C. Adami, R. K. Belew, H. Kitano and C.E. Taylor, Eds., MIT Press, 1998, 109-209.

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Murakawa, M., Yoshizawa, S., Kajitani, I., Yao, X., Kajihara, N., Iwata, M., and Higuchi, T. The GRD chip: Genetic reconfiguration of DSPs for neural network processing. IEEE Transactions on Computers (June 1999). To appear.

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Murakawa, M., Yoshizawa, T., Adachi, T., Suzuki, S., Takasuka, K., Keymeulen, D., and Higuchi, T. Analogue EHW chip for Intermediate Frequency Filter. In Proceedings of the International ConJ~rence on Evolvable Systems, (Sept. 1998), 134-143.

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Sakanashi, H. Salami, M. Iwata, M. Nakaya, S. Yamauchi, T., Inuo, T., Kajihara, N., and Higuchi, T. Evolvable hardware chip for high precision printer image compression In Proceedings of the 15th National Con- J~rence on Artificial Intelligence (AAAI-98), (Madison, Wisconsin, July 1998), 486-491.

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Yao, X. and Higuchi, T. Promises and challenges of evolvable hardware. IEEE Transactions on Systems, Man, and Cybernetics, Part C, 28, 4 (Nov. 1998).

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Cited By

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Simek VRuzicka R(2014)Reconfigurable Platform with Polymorphic Digital Gates and Partial Reconfiguration FeatureProceedings of the 2014 European Modelling Symposium10.1109/EMS.2014.26(501-506)Online publication date: 21-Oct-2014
https://dl.acm.org/doi/10.1109/EMS.2014.26
Lin YChen J(2012)A hardware design of neuromolecular network with enhanced evolvabilityJournal of Electrical and Computer Engineering10.1155/2012/2787352012(3-3)Online publication date: 1-Jan-2012
https://dl.acm.org/doi/10.1155/2012/278735
Lin YChen JHuang C(2009)Design and implementation of an artificial neuromolecular chip and its applications to pattern classification problemsNeurocomputing10.1016/j.neucom.2008.09.01772:13-15(2892-2901)Online publication date: 1-Aug-2009
https://dl.acm.org/doi/10.1016/j.neucom.2008.09.017
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Index Terms

Evolvable hardware chips for industrial applications
1. Hardware
  1. Emerging technologies
  2. Integrated circuits

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Evolvable Hardware (EHW) refers to HW design and self-reconfiguration using evolutionary/genetic mechanisms. The paper presents an overview of some key concepts of EHW, comments on selected applications, and presents a perspective on the development of ...
Complete hardware evolution based SoPC for evolvable hardware

First CHE for EH based on the CGP model, and hence, the complete algorithm, including the required memory is realized on the CLB logic of a single FPGA.No other hard/soft resource (microcontroller or Power PC) usage for the implementation.Memory ...

Reviews

Reviewer: Andrew Donald Booth

This interesting but superficial paper discusses the design and use of “evolvable” chips. The algorithm proposed is based on genetic mutation, and the authors show how such devices can speed up such things as neural net analyzers and goal-seeking automata. If these chips ever become commercially available, they will produce a revolution in some areas of engineering design.

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Published In

Communications of the ACM Volume 42, Issue 4

April 1999

97 pages

ISSN:0001-0782

EISSN:1557-7317

DOI:10.1145/299157

Editor:
Diane Crawford

Issue’s Table of Contents

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 April 1999

Published in CACM Volume 42, Issue 4

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Cited By

View all

Simek VRuzicka R(2014)Reconfigurable Platform with Polymorphic Digital Gates and Partial Reconfiguration FeatureProceedings of the 2014 European Modelling Symposium10.1109/EMS.2014.26(501-506)Online publication date: 21-Oct-2014
https://dl.acm.org/doi/10.1109/EMS.2014.26
Lin YChen J(2012)A hardware design of neuromolecular network with enhanced evolvabilityJournal of Electrical and Computer Engineering10.1155/2012/2787352012(3-3)Online publication date: 1-Jan-2012
https://dl.acm.org/doi/10.1155/2012/278735
Lin YChen JHuang C(2009)Design and implementation of an artificial neuromolecular chip and its applications to pattern classification problemsNeurocomputing10.1016/j.neucom.2008.09.01772:13-15(2892-2901)Online publication date: 1-Aug-2009
https://dl.acm.org/doi/10.1016/j.neucom.2008.09.017
Lin YChen J(2009)ReviewExpert Systems with Applications: An International Journal10.1016/j.eswa.2008.01.07736:2(2568-2583)Online publication date: 1-Mar-2009
https://dl.acm.org/doi/10.1016/j.eswa.2008.01.077
Kaufmann PPlatzner MRyan C(2008)Advanced techniques for the creation and propagation of modules in cartesian genetic programmingProceedings of the 10th annual conference on Genetic and evolutionary computation10.1145/1389095.1389334(1219-1226)Online publication date: 13-Jul-2008
https://dl.acm.org/doi/10.1145/1389095.1389334
Kaufmann PPlatzner M(2007)Toward self-adaptive embedded systemsProceedings of the 20th international conference on Architecture of computing systems10.5555/1763274.1763289(199-208)Online publication date: 12-Mar-2007
https://dl.acm.org/doi/10.5555/1763274.1763289
Kaufmann PPlatzner M(2007)Toward Self-adaptive Embedded Systems: Multi-objective Hardware EvolutionArchitecture of Computing Systems - ARCS 200710.1007/978-3-540-71270-1_15(199-208)Online publication date: 2007
https://doi.org/10.1007/978-3-540-71270-1_15
Kajitani IIwata MHiguchi T(2006)A GA Hardware Engine and Its ApplicationsEvolvable Hardware10.1007/0-387-31238-2_3(41-63)Online publication date: 2006
https://doi.org/10.1007/0-387-31238-2_3
Salami MHendtlass T(2005)The Fast Evaluation Strategy for Evolvable HardwareGenetic Programming and Evolvable Machines10.1007/s10710-005-7578-16:2(139-162)Online publication date: 1-Jun-2005
https://dl.acm.org/doi/10.1007/s10710-005-7578-1
TAN KWANG LLEE T(2004)FPGA-BASED AUTONOMOUS ROBOT NAVIGATION VIA INTRINSIC EVOLUTIONApplied Artificial Intelligence10.1080/0883951049027892518:2(129-155)Online publication date: Feb-2004
https://doi.org/10.1080/08839510490278925
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References

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Index Terms

Recommendations

Toward Evolvable Hardware Chips: Experiments with a Programmable Transistor Array

Evolvable Hardware: From On-Chip Circuit Synthesis to Evolvable Space Systems

Complete hardware evolution based SoPC for evolvable hardware

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