A parallel multidimensional weighted histogram analysis method

 

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dc.contributor.advisor Kuttel, Michelle Mary en_ZA
dc.contributor.author Potgieter, Andrew en_ZA
dc.date.accessioned 2015-07-03T08:36:00Z
dc.date.available 2015-07-03T08:36:00Z
dc.date.issued 2014 en_ZA
dc.identifier.citation Potgieter, A. 2014. A parallel multidimensional weighted histogram analysis method. University of Cape Town. en_ZA
dc.identifier.uri http://hdl.handle.net/11427/13362
dc.description Includes bibliographical references. en_ZA
dc.description.abstract 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. en_ZA
dc.language.iso eng en_ZA
dc.subject.other Information Technology en_ZA
dc.title A parallel multidimensional weighted histogram analysis method en_ZA
dc.type Thesis / Dissertation en_ZA
uct.type.publication Research en_ZA
uct.type.resource Thesis en_ZA
dc.publisher.institution University of Cape Town
dc.publisher.faculty Faculty of Science en_ZA
dc.publisher.department Department of Computer Science en_ZA
dc.type.qualificationlevel Masters en_ZA
dc.type.qualificationname MSc en_ZA
uct.type.filetype Text
uct.type.filetype Image


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