Full Text Available
Note: Clicking the button above will open the full text document at the original institutional repository in a new window.
A parallel multidimensional weighted histogram analysis method
Includes bibliographical references.
Saved in:
| Main Author: | |
|---|---|
| Other Authors: | |
| Format: | Thesis |
| Language: | English |
| Published: |
Department of Computer Science
2015
|
| Subjects: | |
| Tags: |
No Tags, Be the first to tag this record!
|
| _version_ | 1867613146217185280 |
|---|---|
| access_status_str | Open Access |
| author | Potgieter, Andrew |
| author2 | Kuttel, Michelle Mary |
| author_browse | Kuttel, Michelle Mary Potgieter, Andrew |
| author_facet | Kuttel, Michelle Mary Potgieter, Andrew |
| author_sort | Potgieter, Andrew |
| collection | Thesis |
| description | Includes bibliographical references. |
| format | Thesis |
| id | oai:open.uct.ac.za:11427/13362 |
| institution | University of Cape Town (South Africa) |
| language | eng |
| last_indexed | 2026-06-10T12:31:30.019Z |
| license_str | Not specified — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UCTD — University of Cape Town Open Access Repository |
| publishDate | 2015 |
| publishDateRange | 2015 |
| publishDateSort | 2015 |
| publisher | Department of Computer Science |
| publisherStr | Department of Computer Science |
| record_format | dspace |
| source_str | UCTD — University of Cape Town Open Access Repository |
| spelling | oai:open.uct.ac.za:11427/13362 A parallel multidimensional weighted histogram analysis method Potgieter, Andrew Kuttel, Michelle Mary Information Technology Includes bibliographical references. 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. 2015-07-03T08:36:00Z 2015-07-03T08:36:00Z 2014 Master Thesis Masters MSc http://hdl.handle.net/11427/13362 eng application/pdf Department of Computer Science Faculty of Science University of Cape Town |
| spellingShingle | Information Technology Potgieter, Andrew A parallel multidimensional weighted histogram analysis method |
| thesis_degree_str | Master's |
| title | A parallel multidimensional weighted histogram analysis method |
| title_full | A parallel multidimensional weighted histogram analysis method |
| title_fullStr | A parallel multidimensional weighted histogram analysis method |
| title_full_unstemmed | A parallel multidimensional weighted histogram analysis method |
| title_short | A parallel multidimensional weighted histogram analysis method |
| title_sort | parallel multidimensional weighted histogram analysis method |
| topic | Information Technology |
| url | http://hdl.handle.net/11427/13362 |
| work_keys_str_mv | AT potgieterandrew aparallelmultidimensionalweightedhistogramanalysismethod AT potgieterandrew parallelmultidimensionalweightedhistogramanalysismethod |