A Study of CUDA Implementation in the Finite Element Methods

碩士 === 國立中正大學 === 數學系應用數學研究所 === 105 === In this paper, we update the work in [2] in 2012 and discuss the progress of NVIDIA’s CUDA from 2012 to 2016, which includes the software CUDA-toolkit and the hardware of GPUs. The model problems considered for speedup performance are the Laplace equation and...

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Main Author: 劉家植
Other Authors: 陳慈芬
Format: Others
Language:en_US
Published: 2017
Online Access:http://ndltd.ncl.edu.tw/handle/22958960082572653260
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spelling ndltd-TW-105CCU005070082017-10-14T04:28:32Z http://ndltd.ncl.edu.tw/handle/22958960082572653260 A Study of CUDA Implementation in the Finite Element Methods 劉家植 碩士 國立中正大學 數學系應用數學研究所 105 In this paper, we update the work in [2] in 2012 and discuss the progress of NVIDIA’s CUDA from 2012 to 2016, which includes the software CUDA-toolkit and the hardware of GPUs. The model problems considered for speedup performance are the Laplace equation and Stokes problem. One of the goal is to study the effect of CUDA programming of the conjugate gradient (CG) method used to solve the symmetric positive definite matrix in Laplace equation. For the Stokes problem, generalized minimal residual (GMRES) method is used to solve non-symmetric matrix. The performance of the CUDA programming will be presented. For more accuracy, double precision is also considered in our computations. 陳慈芬 2017 學位論文 ; thesis 66 en_US
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language en_US
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description 碩士 === 國立中正大學 === 數學系應用數學研究所 === 105 === In this paper, we update the work in [2] in 2012 and discuss the progress of NVIDIA’s CUDA from 2012 to 2016, which includes the software CUDA-toolkit and the hardware of GPUs. The model problems considered for speedup performance are the Laplace equation and Stokes problem. One of the goal is to study the effect of CUDA programming of the conjugate gradient (CG) method used to solve the symmetric positive definite matrix in Laplace equation. For the Stokes problem, generalized minimal residual (GMRES) method is used to solve non-symmetric matrix. The performance of the CUDA programming will be presented. For more accuracy, double precision is also considered in our computations.
author2 陳慈芬
author_facet 陳慈芬
劉家植
author 劉家植
spellingShingle 劉家植
A Study of CUDA Implementation in the Finite Element Methods
author_sort 劉家植
title A Study of CUDA Implementation in the Finite Element Methods
title_short A Study of CUDA Implementation in the Finite Element Methods
title_full A Study of CUDA Implementation in the Finite Element Methods
title_fullStr A Study of CUDA Implementation in the Finite Element Methods
title_full_unstemmed A Study of CUDA Implementation in the Finite Element Methods
title_sort study of cuda implementation in the finite element methods
publishDate 2017
url http://ndltd.ncl.edu.tw/handle/22958960082572653260
work_keys_str_mv AT liújiāzhí astudyofcudaimplementationinthefiniteelementmethods
AT liújiāzhí studyofcudaimplementationinthefiniteelementmethods
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