Evolutionary Approach to Approximate Digital Circuits Design

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F15%3APU116926" target="_blank" >RIV/00216305:26230/15:PU116926 - isvavai.cz</a>

Výsledek na webu

<a href="http://www.fit.vutbr.cz/research/pubs/all.php?id=10406" target="_blank" >http://www.fit.vutbr.cz/research/pubs/all.php?id=10406</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/TEVC.2014.2336175" target="_blank" >10.1109/TEVC.2014.2336175</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Evolutionary Approach to Approximate Digital Circuits Design

Popis výsledku v původním jazyce

In approximate computing, the requirement of perfect functional behavior can be relaxed because some applications are inherently error resilient. Approximate circuits, which fall into the approximate computing paradigm, are designed in such a way that they do not fully implement the logic behavior given by the specification and hence their accuracy can be exchanged for lower area, delay or power consumption.  In order to automate the design process, we propose to evolve approximate digital circuits which show a minimal error for a supplied amount of resources. The design process which is based on Cartesian Genetic Programming (CGP) can be repeated many times in order to obtain various tradeoffs between the accuracy and area. A heuristic seeding mechanism is introduced to CGP which allows for  improving not only the quality of evolved circuits, but also reducing the time of evolution. The efficiency of the proposed method is evaluated for the gate as well as the functional level evolution. In particular, approximate multipliers and median circuits which show very good parameters in comparison with other available implementations were constructed by means of the proposed method. 

Název v anglickém jazyce

Evolutionary Approach to Approximate Digital Circuits Design

Popis výsledku anglicky

In approximate computing, the requirement of perfect functional behavior can be relaxed because some applications are inherently error resilient. Approximate circuits, which fall into the approximate computing paradigm, are designed in such a way that they do not fully implement the logic behavior given by the specification and hence their accuracy can be exchanged for lower area, delay or power consumption.  In order to automate the design process, we propose to evolve approximate digital circuits which show a minimal error for a supplied amount of resources. The design process which is based on Cartesian Genetic Programming (CGP) can be repeated many times in order to obtain various tradeoffs between the accuracy and area. A heuristic seeding mechanism is introduced to CGP which allows for  improving not only the quality of evolved circuits, but also reducing the time of evolution. The efficiency of the proposed method is evaluated for the gate as well as the functional level evolution. In particular, approximate multipliers and median circuits which show very good parameters in comparison with other available implementations were constructed by means of the proposed method. 

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

<a href="/cs/project/ED1.1.00%2F02.0070" target="_blank" >ED1.1.00/02.0070: Centrum excelence IT4Innovations</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2015

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION

ISSN

1089-778X

e-ISSN

1941-0026

Svazek periodika

19

Číslo periodika v rámci svazku

3

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

13

Strana od-do

432-444

Kód UT WoS článku

000356517700009

EID výsledku v databázi Scopus

2-s2.0-84930965638