Implementation of a High-Performance Genetic Algorithm Processor for Hardware Optimization
Summary :
In this paper, a hardware-oriented Genetic Algorithm (GA) was proposed in order to save the hardware resources and to reduce the execution time of GAP. Based on steady-state model among continuous generation model, the proposed GA used modified tournament selection, as well as special survival condition, with replaced whenever the offspring's fitness is better than worse-fit parent's. The proposed algorithm shows more than 30% in convergence speed over the conventional algorithm. Finally, by employing the efficient pipeline parallelization and handshaking protocol in proposed GAP, above 30% of the computation speed-up can be achieved over survival-based GA which runs one million crossovers per second (1 MHz), when device speed and size of application are taken into account on prototype. It would be used for high speed processing such of central processor of evolvable hardware, robot control and many optimization problems.
- Publication
- IEICE TRANSACTIONS on Electronics Vol.E85-C No.1 pp.195-203
- Publication Date
- 2002/01/01
- Publicized
- Online ISSN
- DOI
- Type of Manuscript
- PAPER
- Category
- Electronic Circuits
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Jinjung KIM, Yunho CHOI, Chongho LEE, Duckjin CHUNG, "Implementation of a High-Performance Genetic Algorithm Processor for Hardware Optimization" in IEICE TRANSACTIONS on Electronics,
vol. E85-C, no. 1, pp. 195-203, January 2002, doi: .
Abstract: In this paper, a hardware-oriented Genetic Algorithm (GA) was proposed in order to save the hardware resources and to reduce the execution time of GAP. Based on steady-state model among continuous generation model, the proposed GA used modified tournament selection, as well as special survival condition, with replaced whenever the offspring's fitness is better than worse-fit parent's. The proposed algorithm shows more than 30% in convergence speed over the conventional algorithm. Finally, by employing the efficient pipeline parallelization and handshaking protocol in proposed GAP, above 30% of the computation speed-up can be achieved over survival-based GA which runs one million crossovers per second (1 MHz), when device speed and size of application are taken into account on prototype. It would be used for high speed processing such of central processor of evolvable hardware, robot control and many optimization problems.
URL: https://global.ieice.org/en_transactions/electronics/10.1587/e85-c_1_195/_p
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@ARTICLE{e85-c_1_195,
author={Jinjung KIM, Yunho CHOI, Chongho LEE, Duckjin CHUNG, },
journal={IEICE TRANSACTIONS on Electronics},
title={Implementation of a High-Performance Genetic Algorithm Processor for Hardware Optimization},
year={2002},
volume={E85-C},
number={1},
pages={195-203},
abstract={In this paper, a hardware-oriented Genetic Algorithm (GA) was proposed in order to save the hardware resources and to reduce the execution time of GAP. Based on steady-state model among continuous generation model, the proposed GA used modified tournament selection, as well as special survival condition, with replaced whenever the offspring's fitness is better than worse-fit parent's. The proposed algorithm shows more than 30% in convergence speed over the conventional algorithm. Finally, by employing the efficient pipeline parallelization and handshaking protocol in proposed GAP, above 30% of the computation speed-up can be achieved over survival-based GA which runs one million crossovers per second (1 MHz), when device speed and size of application are taken into account on prototype. It would be used for high speed processing such of central processor of evolvable hardware, robot control and many optimization problems.},
keywords={},
doi={},
ISSN={},
month={January},}
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TY - JOUR
TI - Implementation of a High-Performance Genetic Algorithm Processor for Hardware Optimization
T2 - IEICE TRANSACTIONS on Electronics
SP - 195
EP - 203
AU - Jinjung KIM
AU - Yunho CHOI
AU - Chongho LEE
AU - Duckjin CHUNG
PY - 2002
DO -
JO - IEICE TRANSACTIONS on Electronics
SN -
VL - E85-C
IS - 1
JA - IEICE TRANSACTIONS on Electronics
Y1 - January 2002
AB - In this paper, a hardware-oriented Genetic Algorithm (GA) was proposed in order to save the hardware resources and to reduce the execution time of GAP. Based on steady-state model among continuous generation model, the proposed GA used modified tournament selection, as well as special survival condition, with replaced whenever the offspring's fitness is better than worse-fit parent's. The proposed algorithm shows more than 30% in convergence speed over the conventional algorithm. Finally, by employing the efficient pipeline parallelization and handshaking protocol in proposed GAP, above 30% of the computation speed-up can be achieved over survival-based GA which runs one million crossovers per second (1 MHz), when device speed and size of application are taken into account on prototype. It would be used for high speed processing such of central processor of evolvable hardware, robot control and many optimization problems.
ER -
English
