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DOBAI, R. SEKANINA, L.
Original Title
Towards Evolvable Systems Based on the Xilinx Zynq Platform
Type
article in a collection out of WoS and Scopus
Language
English
Original Abstract
Field programmable gate arrays (FPGAs) are considered as a good platform for digital evolvable hardware systems. Researchers introduced virtual reconfigurable circuits as the response to the insufficient support of partial reconfiguration in early FPGAs. Later, the features of FPGAs allowed the designers to develop evolvable systems fully exploiting native reconfiguration infrastructures. Xilinx recently introduced a new platform called Zynq-7000 all programmable (AP) system-on-chip (SoC) which has the potential to become the next revolutionary step in evolvable hardware design. The paper analyzes Zynq-7000 AP SoC from the perspective of an evolvable hardware designer. Several scenarios are described of how to implement evolvable systems on a developmental board equipped with this programmable SoC. These scenarios are evaluated in terms of area overhead, execution time, reconfiguration time and throughput. The resulting observations should be useful for those who are going to develop real-world evolvable systems on the Zynq-7000 AP SoC platform.
Keywords
FPGA, evolvable hardware, reconfiguration, digital circuit, image filter, zynq
Authors
DOBAI, R.; SEKANINA, L.
RIV year
2013
Released
16. 4. 2013
Publisher
IEEE Computational Intelligence Society
Location
Singapur
ISBN
978-1-4673-5869-9
Book
2013 IEEE International Conference on Evolvable Systems (ICES)
Edition
Proceedings of the 2013 IEEE Symposium Series on Computational Intelligence (SSCI)
Pages from
89
Pages to
95
Pages count
7
URL
https://www.fit.vut.cz/research/publication/10194/
BibTex
@inproceedings{BUT103436, author="Roland {Dobai} and Lukáš {Sekanina}", title="Towards Evolvable Systems Based on the Xilinx Zynq Platform", booktitle="2013 IEEE International Conference on Evolvable Systems (ICES)", year="2013", series="Proceedings of the 2013 IEEE Symposium Series on Computational Intelligence (SSCI)", pages="89--95", publisher="IEEE Computational Intelligence Society", address="Singapur", doi="10.1109/ICES.2013.6613287", isbn="978-1-4673-5869-9", url="https://www.fit.vut.cz/research/publication/10194/" }