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Synopsis
The explosive growth in the programming capabilities and raw processing power of Graphical Processing Units has opened up new avenues for their use in non-graphic applications. The combination of large stream of data and the need for 3D vector operations make the primitive shape fit algorithms excellent candidates for processing via a GPU. The work presented in this research investigates the use of the parallel processing capabilities of the GPU in expediting specific computations involved in the fitting procedure. The least squares fit algorithms for the circle, sphere, cylinder, plane, cone and torus have been implemented on the GPU using NVIDIA’s Compute Unified Device Architecture (CUDA). The implementations are benchmarked against those on a CPU which are carried out using C++. The Gauss Newton minimization algorithm is used to obtain the best fit parameters for each of the aforementioned primitives. The computation times for the two implementations are compared. It is demonstrated that the GPU is about 3-4 times faster than the CPU for a relatively simple geometry such as the circle while the factor scales to about 14 for a torus which is more complex.
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About the Author
Meghashyam Panyam received his B.E. (2004) and M.Sc. (2007) in Mechanical Engineering from M.S.R.Institute of Technology, India and Clemson University, USA, respectively. He is currently pursuing his PhD in Mechanical Engineering at Clemson University in South Carolina, USA. His research focuses on nonlinear vibratory energy harvesting.
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- PublisherLAP LAMBERT Academic Publishing
- Publication date2014
- ISBN 10 3659643262
- ISBN 13 9783659643262
- BindingPaperback
- LanguageEnglish
- Number of pages128
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Least Squares Fitting of Analytic Primitives on a GPU
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LAP LAMBERT Academic Publishing Dez 2014, 2014
ISBN 10: 3659643262
ISBN 13: 9783659643262
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Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The explosive growth in the programming capabilities and raw processing power of Graphical Processing Units has opened up new avenues for their use in non-graphic applications. The combination of large stream of data and the need for 3D vector operations make the primitive shape fit algorithms excellent candidates for processing via a GPU. The work presented in this research investigates the use of the parallel processing capabilities of the GPU in expediting specific computations involved in the fitting procedure. The least squares fit algorithms for the circle, sphere, cylinder, plane, cone and torus have been implemented on the GPU using NVIDIA's Compute Unified Device Architecture (CUDA). The implementations are benchmarked against those on a CPU which are carried out using C++. The Gauss Newton minimization algorithm is used to obtain the best fit parameters for each of the aforementioned primitives. The computation times for the two implementations are compared. It is demonstrated that the GPU is about 3-4 times faster than the CPU for a relatively simple geometry such as the circle while the factor scales to about 14 for a torus which is more complex. 128 pp. Englisch. Seller Inventory # 9783659643262
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Least Squares Fitting of Analytic Primitives on a GPU
Published by
LAP LAMBERT Academic Publishing, 2014
ISBN 10: 3659643262
ISBN 13: 9783659643262
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Taschenbuch
Seller: AHA-BUCH GmbH, Einbeck, Germany
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The explosive growth in the programming capabilities and raw processing power of Graphical Processing Units has opened up new avenues for their use in non-graphic applications. The combination of large stream of data and the need for 3D vector operations make the primitive shape fit algorithms excellent candidates for processing via a GPU. The work presented in this research investigates the use of the parallel processing capabilities of the GPU in expediting specific computations involved in the fitting procedure. The least squares fit algorithms for the circle, sphere, cylinder, plane, cone and torus have been implemented on the GPU using NVIDIA's Compute Unified Device Architecture (CUDA). The implementations are benchmarked against those on a CPU which are carried out using C++. The Gauss Newton minimization algorithm is used to obtain the best fit parameters for each of the aforementioned primitives. The computation times for the two implementations are compared. It is demonstrated that the GPU is about 3-4 times faster than the CPU for a relatively simple geometry such as the circle while the factor scales to about 14 for a torus which is more complex. Seller Inventory # 9783659643262
Quantity: 1 available
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Least Squares Fitting of Analytic Primitives on a GPU
Published by
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ISBN 10: 3659643262
ISBN 13: 9783659643262
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Seller: moluna, Greven, Germany
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Panyam MeghashyamMeghashyam Panyam received his B.E. (2004) and M.Sc. (2007) in Mechanical Engineering from M.S.R.Institute of Technology, India and Clemson University, USA, respectively. He is currently pursuing his PhD in Mechanica. Seller Inventory # 5170564
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