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Title:OPTIMIZACIJA MEDATOMSKEGA POTENCIALA LENNARD-JONES S PARALELNO DIFERENCIALNO EVOLUCIJO
Authors:Čep, Aleš (Author)
Brest, Janez (Mentor) More about this mentor... New window
Zamuda, Aleš (Co-mentor)
Files:.pdf UNI_Cep_Ales_2011.pdf (1,89 MB)
 
Language:Slovenian
Work type:Bachelor thesis/paper (mb11)
Organization:FERI - Faculty of Electrical Engineering and Computer Science
Abstract:V diplomskem delu predstavljamo optimizacijski algoritem, ki rešuje problem potenciala Lennard-Jones iz področja bioinformatike. Za računanje uporabimo tehnologijo CUDA, ki poveča hitrost računanja, saj izkorišča paralelizacijsko zmogljivost grafičnih procesnih enot. Izbrali smo evolucijski algoritem jDE, ki se je v preteklosti izkazal za zelo uspešnega. Diplomska naloga najprej obravnava sorodna dela iz področja računanja potenciala Lennard-Jones ter področja evolucijskih algoritmov na grafičnih procesnih enotah. Sledi opis potenciala Lennard-Jones in arhitekture CUDA. Na koncu je predstavljena še naša implementacija algoritma in dobljeni rezultati. Naše rezultate smo primerjali z rezultati dveh programov, ki se v celoti izvajata na centralno procesni enoti.
Keywords:diferencialna evolucija, potencial Lennard-Jones, CUDA, bioinformatika, paralelno izvajanje, evolucijski algoritem, jDE, evolucijsko računanje, grafična procesna enota
Year of publishing:2011
Publisher:[A. Čep]
Source:Maribor
UDC:004.6.032.24(043.2)
COBISS_ID:15353622 Link is opened in a new window
NUK URN:URN:SI:UM:DK:0IZRTBLL
Views:2297
Downloads:210
Metadata:XML RDF-CHPDL DC-XML DC-RDF
Categories:KTFMB - FERI
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Secondary language

Language:English
Title:OPTIMIZATION OF LENNARD-JONES ATOM POTENTIAL USING PARALLEL DIFFERENTIAL EVOLUTION
Abstract:In this diploma work we present an optimization algorithm for solving problem of Lennard-Jones energy potential, which falls into field of bioinformatics. We use CUDA architecture to increase computational speed, because it allows us to exploit the parallel capabilities of graphics processing unit. For optimization we have chosen the jDE evolutionary algorithm, which showed great results in the past. First we describe related works in the area of optimization of Lennard-Jones energy potential and evolutionary algorithms on graphics processing unit. In second part we focus on Lennard-Jones potential and CUDA architecture. In the end we present our program and its results, which we compare with results of two other programs that are executed on a central processing unit.
Keywords:differential evolution, potential Lennard-Jones, CUDA, bioinformatics, parallelization, evolution algorithm, jDE, evolution computation, graphics processing unit


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