A parallel multidimensional weighted histogram analysis method

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dc.contributor.advisorKuttel, Michelle Maryen_ZA
dc.contributor.authorPotgieter, Andrewen_ZA
dc.date.accessioned2015-07-03T08:36:00Z
dc.date.available2015-07-03T08:36:00Z
dc.date.issued2014en_ZA
dc.descriptionIncludes bibliographical references.en_ZA
dc.description.abstractThe Weighted Histogram Analysis Method (WHAM) is a technique used to calculate free energy from molecular simulation data. WHAM recombines biased distributions of samples from multiple Umbrella Sampling simulations to yield an estimate of the global unbiased distribution. The WHAM algorithm iterates two coupled, non-linear, equations, until convergence at an acceptable level of accuracy. The equations have quadratic time complexity for a single reaction coordinate. However, this increases exponentially with the number of reaction coordinates under investigation, which makes multidimensional WHAM a computationally expensive procedure. There is potential to use general purpose graphics processing units (GPGPU) to accelerate the execution of the algorithm. Here we develop and evaluate a multidimensional GPGPU WHAM implementation to investigate the potential speed-up attained over its CPU counterpart. In addition, to avoid the cost of multiple Molecular Dynamics simulations and for validation of the implementations we develop a test system to generate samples analogous to Umbrella Sampling simulations. We observe a maximum problem size dependent speed-up of approximately 19 x for the GPGPU optimized WHAM implementation over our single threaded CPU optimized version. We find that the WHAM algorithm is amenable to GPU acceleration, which provides the means to study ever more complex molecular systems in reduced time periods.en_ZA
dc.identifier.apacitationPotgieter, A. (2014). <i>A parallel multidimensional weighted histogram analysis method</i>. (Thesis). University of Cape Town ,Faculty of Science ,Department of Computer Science. Retrieved from http://hdl.handle.net/11427/13362en_ZA
dc.identifier.chicagocitationPotgieter, Andrew. <i>"A parallel multidimensional weighted histogram analysis method."</i> Thesis., University of Cape Town ,Faculty of Science ,Department of Computer Science, 2014. http://hdl.handle.net/11427/13362en_ZA
dc.identifier.citationPotgieter, A. 2014. A parallel multidimensional weighted histogram analysis method. University of Cape Town.en_ZA
dc.identifier.ris TY - Thesis / Dissertation AU - Potgieter, Andrew AB - The Weighted Histogram Analysis Method (WHAM) is a technique used to calculate free energy from molecular simulation data. WHAM recombines biased distributions of samples from multiple Umbrella Sampling simulations to yield an estimate of the global unbiased distribution. The WHAM algorithm iterates two coupled, non-linear, equations, until convergence at an acceptable level of accuracy. The equations have quadratic time complexity for a single reaction coordinate. However, this increases exponentially with the number of reaction coordinates under investigation, which makes multidimensional WHAM a computationally expensive procedure. There is potential to use general purpose graphics processing units (GPGPU) to accelerate the execution of the algorithm. Here we develop and evaluate a multidimensional GPGPU WHAM implementation to investigate the potential speed-up attained over its CPU counterpart. In addition, to avoid the cost of multiple Molecular Dynamics simulations and for validation of the implementations we develop a test system to generate samples analogous to Umbrella Sampling simulations. We observe a maximum problem size dependent speed-up of approximately 19 x for the GPGPU optimized WHAM implementation over our single threaded CPU optimized version. We find that the WHAM algorithm is amenable to GPU acceleration, which provides the means to study ever more complex molecular systems in reduced time periods. DA - 2014 DB - OpenUCT DP - University of Cape Town LK - https://open.uct.ac.za PB - University of Cape Town PY - 2014 T1 - A parallel multidimensional weighted histogram analysis method TI - A parallel multidimensional weighted histogram analysis method UR - http://hdl.handle.net/11427/13362 ER - en_ZA
dc.identifier.urihttp://hdl.handle.net/11427/13362
dc.identifier.vancouvercitationPotgieter A. A parallel multidimensional weighted histogram analysis method. [Thesis]. University of Cape Town ,Faculty of Science ,Department of Computer Science, 2014 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/13362en_ZA
dc.language.isoengen_ZA
dc.publisher.departmentDepartment of Computer Scienceen_ZA
dc.publisher.facultyFaculty of Scienceen_ZA
dc.publisher.institutionUniversity of Cape Town
dc.subject.otherInformation Technologyen_ZA
dc.titleA parallel multidimensional weighted histogram analysis methoden_ZA
dc.typeMaster Thesis
dc.type.qualificationlevelMasters
dc.type.qualificationnameMScen_ZA
uct.type.filetypeText
uct.type.filetypeImage
uct.type.publicationResearchen_ZA
uct.type.resourceThesisen_ZA
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