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Title:Nevroevolucijski algoritem NEAT na grafičnih karticah : magistrsko delo
Authors:ID Sitar, Blaž (Author)
ID Holobar, Aleš (Mentor) More about this mentor... New window
Files:.pdf MAG_Sitar_Blaz_2019.pdf (1,53 MB)
MD5: 963A3853823507F6D5222899FBEA4CB4
PID: 20.500.12556/dkum/40484ae0-07ad-4170-903f-f6e9547d6794
 
Language:Slovenian
Work type:Master's thesis/paper
Typology:2.09 - Master's Thesis
Organization:FERI - Faculty of Electrical Engineering and Computer Science
Abstract:V magistrski nalogi naslavljamo problem implementacije algoritma NeuroEvolution of Augmenting Topologies (NEAT) za delovanje na grafičnih karticah. Algoritem NEAT je genetski algoritem za učenje razvijajočih nevronskih mrež. Izhaja iz področja nevroevolucije, ki v umetni inteligenci uporablja genetske algoritme za generiranje in učenje nevronskih mrež. Algoritem za svoje delovanje porabi veliko strojnih in časovnih virov, zato je implementacija na grafičnih karticah smiselna. Implementacijo smo izvedli v arhitekturi CUDA, ki jo podpirajo grafične kartice podjetja NVIDIA. Hitrost in uspešnost algoritma smo izmerili na petih različnih grafičnih karticah in jo primerjali s hitrostjo in uspešnostjo originalnega algoritma. Ugotovili smo, da je naša implementacija algoritma zadovoljiva, saj je hitrejša in prav toliko uspešna kot originalna implementacija algoritma NEAT.
Keywords:nevroevolucija, NEAT, nevronska mreža, genetski algoritem, CUDA
Place of publishing:Maribor
Place of performance:Maribor
Publisher:[B. Sitar]
Year of publishing:2019
Number of pages:XI, 65 str.
PID:20.500.12556/DKUM-74852 New window
UDC:004.8.021(043.2)
COBISS.SI-ID:22891030 New window
NUK URN:URN:SI:UM:DK:NI0O6N2D
Publication date in DKUM:21.11.2019
Views:1631
Downloads:166
Metadata:XML DC-XML DC-RDF
Categories:KTFMB - FERI
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Licences

License:CC BY-NC-ND 4.0, Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
Link:http://creativecommons.org/licenses/by-nc-nd/4.0/
Description:The most restrictive Creative Commons license. This only allows people to download and share the work for no commercial gain and for no other purposes.
Licensing start date:10.09.2019

Secondary language

Language:English
Title:Neuroevolution algorithm neat on graphics cards
Abstract:We address the problem of NeuroEvolution of Augmenting Topologies (NEAT) algorithm implementation for operating on graphics cards. NEAT is a genetic algorithm for learning and evolving neural networks. It’s a member of the neuroevolution algorithms which use genetic algorithms to learn and evolve neural networks in the field of artificial intelligence. Algorithm uses a lot of resources for its operation and is, therefore, suitable for implementation on graphics cards. We implemented it on a CUDA architecture, which is supported by NVIDIA graphics cards. We measured the speed and performance of the algorithm on five different graphics cards and compared it to the speed and performance of the original algorithm. Our implementation is satisfactory because it is faster than and just as efficient as the original NEAT implementation.
Keywords:neuroevolution, NEAT, neural network, genetic algorithm, CUDA


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