Geodesic
Parallelization technologies for solving three-dimensional boundary value problems on quasi-structured grids using the CPU+GPU hybrid computing environment
Numerical methods and programming, Tome 17 (2016) no. 1, pp. 65-71 Cet article a éte moissonné depuis la source Math-Net.Ru

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When parallelizing the solution processes of solving three-dimensional boundary value problems on quasi-structured grids by the method of decomposition of the computational domain into subdomains without imposition, the most time consuming computational procedure is a solution of subproblems in subdomains. The application of parallelepiped quasi-structured grids makes it possible to use the rapidly convergent method of alternating directions. The parallelization of iterative processes on subdomains is performed on CPU using MPI. In order to solve the subproblems, we propose to use the graphics accelerators (GPU). Experimental results of using the graphics accelerators to solve the subproblems by Peaceman–Rachford method are discussed. The computational acceleration achieved on the CPU+GPU hybrid computing environment is experimentally estimated compared to using the CPU only.
Keywords: boundary value problems, domain decomposition methods, Poincare–Steklov equation, quasi-structured grids, Peaceman–Rachford method, graphics accelerators. 
@article{VMP_2016_17_1_a6,
     author = {I. A. Klimonov and V. D. Korneev and V. M. Sveshnikov},
     title = {Parallelization technologies for solving three-dimensional boundary value problems on quasi-structured grids using the {CPU+GPU} hybrid computing environment},
     journal = {Numerical methods and programming},
     pages = {65--71},
     year = {2016},
     volume = {17},
     number = {1},
     language = {ru},
     url = {http://geodesic.mathdoc.fr/item/VMP_2016_17_1_a6/}
}
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I. A. Klimonov; V. D. Korneev; V. M. Sveshnikov. Parallelization technologies for solving three-dimensional boundary value problems on quasi-structured grids using the CPU+GPU hybrid computing environment. Numerical methods and programming, Tome 17 (2016) no. 1, pp. 65-71. http://geodesic.mathdoc.fr/item/VMP_2016_17_1_a6/