Evolutionary Functional Approximation of Circuits Implemented into FPGAs
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F16%3APU121666" target="_blank" >RIV/00216305:26230/16:PU121666 - isvavai.cz</a>
Výsledek na webu
<a href="http://www.fit.vutbr.cz/research/pubs/all.php?id=11243" target="_blank" >http://www.fit.vutbr.cz/research/pubs/all.php?id=11243</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/SSCI.2016.7850173" target="_blank" >10.1109/SSCI.2016.7850173</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Evolutionary Functional Approximation of Circuits Implemented into FPGAs
Popis výsledku v původním jazyce
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.
Název v anglickém jazyce
Evolutionary Functional Approximation of Circuits Implemented into FPGAs
Popis výsledku anglicky
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.
Klasifikace
Druh
D - Stať ve sborníku
CEP obor
—
OECD FORD obor
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Návaznosti výsledku
Projekt
Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.
Návaznosti
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Ostatní
Rok uplatnění
2016
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název statě ve sborníku
2016 IEEE Symposium Series on Computational Intelligence
ISBN
978-1-5090-4240-1
ISSN
—
e-ISSN
—
Počet stran výsledku
8
Strana od-do
1-8
Název nakladatele
Institute of Electrical and Electronics Engineers
Místo vydání
Athens
Místo konání akce
Athens
Datum konání akce
6. 12. 2016
Typ akce podle státní příslušnosti
WRD - Celosvětová akce
Kód UT WoS článku
000400488302079