On Evolutionary Approximation of Sigmoid Function for HW/SW Embedded Systems

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F17%3APU123658" target="_blank" >RIV/00216305:26230/17:PU123658 - isvavai.cz</a>
Result on the web
<a href="http://www.fit.vutbr.cz/research/pubs/all.php?id=11298" target="_blank" >http://www.fit.vutbr.cz/research/pubs/all.php?id=11298</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-55696-3_22" target="_blank" >10.1007/978-3-319-55696-3_22</a>

Result language
angličtina
Original language name
On Evolutionary Approximation of Sigmoid Function for HW/SW Embedded Systems
Original language description
Providing machine learning capabilities on low cost electronic devices is a challenging goal especially in the context of the Internet of Things paradigm. In order to deliver high performance machine intelligence on low power devices, suitable hardware accelerators have to be introduced. In this paper, we developed a method enabling to evolve a hardware implementation together with a corresponding software controller for key components of smart embedded systems. The proposed approach is based on a multi-objective design space exploration conducted by means of extended linear genetic programming. The approach was evaluated in the task of approximate sigmoid function design which is an important component of hardware implementations of neural networks. During these experiments, we automatically re-discovered some approximate sigmoid functions known from the literature. The method was implemented as an extension of an existing platform supporting concurrent evolution of hardware and software of embedded systems.
Czech name
—
Czech description
—

Project
<a href="/en/project/GA16-17538S" target="_blank" >GA16-17538S: Relaxed equivalence checking for approximate computing</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2017
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
20th European Conference on Genetic Programming, EuroGP 2017
ISBN
978-3-319-55696-3
ISSN
—
e-ISSN
—
Number of pages
16
Pages from-to
343-358
Publisher name
Springer International Publishing
Place of publication
Berlin
Event location
Amsterdam
Event date
Apr 19, 2017
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000413012200022

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