Ebook: Parallel Computational Technologies: 11th International Conference, PCT 2017, Kazan, Russia, April 3–7, 2017, Revised Selected Papers
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- Series: Communications in Computer and Information Science
- Year: 2017
- Publisher: Springer
- Edition: 1st
- Language: English
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This book constitutes the refereed proceedings of the 11th International Conference on Parallel Computational Technologies, PCT 2017, held in Kazan, Russia, in April 2017.
The parallel CPU+multiGPU implementation of the Implicitly Restarted Arnoldi method (IRA) is presented in the paper. We focus on the problem of implementing an efficient method for large scale non-symmetric eigenvalue problems arising in linear stability and Floquet theory analysis in fluid dynamics problems. We give brief details about the problem in both cases. We use and cross-compare different methods to Read more...
The 24 revised full papers presented were carefully reviewed and selected from 167 submissions. The papers are organized in topical sections on high performance architectures, tools and technologies; parallel numerical algorithms; supercomputer simulation.
The parallel CPU+multiGPU implementation of the Implicitly Restarted Arnoldi method (IRA) is presented in the paper. We focus on the problem of implementing an efficient method for large scale non-symmetric eigenvalue problems arising in linear stability and Floquet theory analysis in fluid dynamics problems. We give brief details about the problem in both cases. We use and cross-compare different methods to Read more...
Abstract: The parallel CPU+multiGPU implementation of the Implicitly Restarted Arnoldi method (IRA) is presented in the paper. We focus on the problem of implementing an efficient method for large scale non-symmetric eigenvalue problems arising in linear stability and Floquet theory analysis in fluid dynamics problems. We give brief details about the problem in both cases. We use and cross-compare different methods to implement QR shifts with polynomial filtering. Then we conduct a benchmark on standard non-symmetric matrices. The presented results give insight on the best choice of the method of polynomial filters. It turns out that a polynomial filter is essential to accelerate computations in fluid dynamics stability problems as well as to increase the Krylov space dimension. However, some knowledge about the spectral radius of the problem is required. Further, we investigate the parallel efficiency of the method for single-GPU and multi-GPU modes using the problems previously considered. It is shown that the implementation of Givens rotations on one GPU for QR computations (of a Hessenberg matrix) is essential in order to achieve high speed for a considerable Krylov subspace dimension. In the final part we present some results regarding the application of the IRA polynomial filtered method to linear stability and Floquet analysis for large fluid dynamics problem with parallel efficiency comparison on multi-GPU architecture