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VAŠÍČEK, Z. MRÁZEK, V. SEKANINA, L.
Original Title
Evolutionary Functional Approximation of Circuits Implemented into FPGAs
Type
conference paper
Language
English
Original Abstract
In many applications it is acceptable to allow a small error in the result if significant improvements are obtained in terms of performance, area or energy efficiency. Exploiting this principle is particularly important for FPGA-based solutions that are inherently subject to many resources- oriented constraints. This paper devises an automated method that enables to approximate circuit components which are often implemented in multiple instances in FPGA-based accelerators. The approximation process starts with a fully functional gate-level circuit, which is approximated by means of Cartesian Genetic Programming reflecting the error metric and constraints formulated by the user. The evolved circuits are then implemented for a particular FPGA by common FPGA synthesis and optimization tools. It is shown using five different FPGA tools, that the approximations obtained by CGP working at the gate level are preserved at the level look-up tables of FPGAs. The proposed method is evaluated in the task of 8-bit adder, 8-bit multiplier, 9-input median and 25-input median approximation.
Keywords
functional approximation evolutionary algorithm equivalence FPGA synthesis
Authors
VAŠÍČEK, Z.; MRÁZEK, V.; SEKANINA, L.
Released
15. 8. 2016
Publisher
Institute of Electrical and Electronics Engineers
Location
Athens
ISBN
978-1-5090-4240-1
Book
2016 IEEE Symposium Series on Computational Intelligence
Pages from
1
Pages to
8
Pages count
URL
https://www.fit.vut.cz/research/publication/11243/
BibTex
@inproceedings{BUT131010, author="Zdeněk {Vašíček} and Vojtěch {Mrázek} and Lukáš {Sekanina}", title="Evolutionary Functional Approximation of Circuits Implemented into FPGAs", booktitle="2016 IEEE Symposium Series on Computational Intelligence", year="2016", pages="1--8", publisher="Institute of Electrical and Electronics Engineers", address="Athens", doi="10.1109/SSCI.2016.7850173", isbn="978-1-5090-4240-1", url="https://www.fit.vut.cz/research/publication/11243/" }