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, "Parallel Implementation of Dynamic Relaxation with CUDA", in , (Editors), "Proceedings of the Fifth International Conference on Parallel, Distributed, Grid and Cloud Computing for Engineering", Civil-Comp Press, Stirlingshire, UK, Paper 35, 2017. doi:10.4203/ccp.111.35

Keywords: dynamic relaxation, parallel implementation, CUDA, asynchronous parallel algorithm.

Summary

The dynamic relaxation method has been widely used for the design and analysis of cable-membrane structures. The method iteratively determines a static solution, therefore the parallelization of the method can speed up the analysis process. The method has already been parallelized with the MPI environment. This paper discusses a new parallelization approach, which is programmed with the NVIDIA CUDA API and executed on a GPU system. Since a GPU system has a large number of cores and a separate memory from the computer therefore the original dynamic relaxation method has to be reorganized. The paper also discusses some performance measurements of the dynamic relaxation method on GPU systems.

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Front Page Browse CCP CSETS CTR IJRT Other Authors Search Purchase Guide FAQ Contact us	Civil-Comp Proceedings ISSN 1759-3433 CCP: 111 PROCEEDINGS OF THE FIFTH INTERNATIONAL CONFERENCE ON PARALLEL, DISTRIBUTED, GRID AND CLOUD COMPUTING FOR ENGINEERING Edited by: Paper 35 Parallel Implementation of Dynamic Relaxation with CUDA P. Iványi Faculty of Engineering and Information Technology, University of Pécs, Hungary doi:10.4203/ccp.111.35 purchase the full-text of this paper Full Bibliographic Reference for this paper , "Parallel Implementation of Dynamic Relaxation with CUDA", in , (Editors), "Proceedings of the Fifth International Conference on Parallel, Distributed, Grid and Cloud Computing for Engineering", Civil-Comp Press, Stirlingshire, UK, Paper 35, 2017. doi:10.4203/ccp.111.35 Keywords: dynamic relaxation, parallel implementation, CUDA, asynchronous parallel algorithm. Summary The dynamic relaxation method has been widely used for the design and analysis of cable-membrane structures. The method iteratively determines a static solution, therefore the parallelization of the method can speed up the analysis process. The method has already been parallelized with the MPI environment. This paper discusses a new parallelization approach, which is programmed with the NVIDIA CUDA API and executed on a GPU system. Since a GPU system has a large number of cores and a separate memory from the computer therefore the original dynamic relaxation method has to be reorganized. The paper also discusses some performance measurements of the dynamic relaxation method on GPU systems. purchase the full-text of this paper (price £22) go to the previous paper go to the next paper return to the table of contents return to the book description purchase this book (price £45 +P&P)
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