Vzporedni genetski algoritem v OpenCL za simulacijo molekulske dinamike

diplomsko delo

Tine Erent (Author), Nejc Ilc (Mentor), Davor Sluga (Co-mentor)

Abstract

V diplomskem delu smo razvili vzporedni genetski algoritem, ki se izvaja na heterogenih računalniških arhitekturah za potrebe simulacije molekulske dinamike. Razviti algoritem uporablja empirično cenilno funkcijo za ocenjevanje rešitev. Simulirali smo sidranje molekul v receptorsko mesto proteina in iskali optimalen položaj molekule. Uporabili smo razvojno ogrodje OpenCL. Analizirali smo konvergenco in učinkovitost algoritma. Uporabljeno merilo učinkovitosti je bil izvajalni čas simulacije. Za testne primere smo uporabili dva liganda. Algoritem smo preizkusili in ovrednotili na dveh grafičnih pospeševalnikih in večjedrnem procesorju. Vzporedni algoritem konvergira in vrača pričakovane rezultate. Za učinkovitejšo rabo grafične procesne enote in večje pohitritve je potrebno algoritem dodatno optimizirati.

Keywords

OpenCL;molekulska dinamika;univerzitetni študij;diplomske naloge;

Data

Language:	Slovenian
Year of publishing:	2022
Typology:	2.11 - Undergraduate Thesis
Organization:	UL FRI - Faculty of Computer and Information Science
Publisher:	[T. Erent]
UDC:	004.021(043.2)
COBISS:	99473667
Views:	150
Downloads:	32
Average score:	0 (0 votes)
Metadata:

Other data

Secondary language:	English
Secondary title:	Parallel genetic algorithm in OpenCL for simulating molecular dynamics
Secondary abstract:	In this thesis we developed a parallel genetic algorithm which can run on heterogeneous systems to simulate molecular dynamics. The algorithm uses an empirical scoring function. We simulated molecule docking to a receptor protein and searched for optimal molecule position. We used OpenCL framework. We analysed the convergence and efficiency of the algorithm. We were primarily concerned with the simulation execution time. We used two ligands as test cases. The algorithm was evaluated on two graphics accelerators and a multi-core processor. Parallel algorithm converges and returns the expected results. For more efficient use of a graphics processing unit and achieving better speedup the algorithm needs further optimization.
Secondary keywords:	genetic algorithm;OpenCL;molecular dynamics;computer science;diploma;Genetski algoritmi;Vzporedni algoritmi;Računalništvo;Univerzitetna in visokošolska dela;
Type (COBISS):	Bachelor thesis/paper
Study programme:	1000468
Thesis comment:	Univ. v Ljubljani, Fak. za računalništvo in informatiko
Pages:	44 str.
ID:	14657170