An Iterative Parallel Solver in GPU Applied to Frequency Domain Linear Water Wave Problems by the Boundary Element Method
Metadatos
Afficher la notice complèteAuteur
Molina Moya, Jorge Antonio; Martínez Castro, Alejandro Enrique; Ortiz Rossini, Pablo GregorioEditorial
Frontiers Media
Materia
GMRES (generalized minimal residual) algorithm CUDA (compute unified device architecture) GPU (CUDA)
Date
2018-11-26Referencia bibliográfica
Molina-Moya J, Martínez-Castro AE and Ortiz P (2018). Front. Built Environ. 4:69. [https://doi.org/10.3389/fbuil.2018.00069]
Patrocinador
MINECO/FEDER project BIA2015-64994-PRésumé
In this paper a parallel iterative solver based on the Generalized Minimum Residual
Method (GMRES) with complex-valued coefficients is explored, with applications to the
Boundary Element Method (BEM). The solver is designed to be executed in a GPU
(Graphic Processing Unit) device, exploiting its massively parallel capabilities. The BEM
is a competitive method in terms of reduction in the number of degrees of freedom.
Nonetheless, the BEM shows disadvantages when the dimension of the system grows,
due to the particular structure of the system matrix. With difference to other acceleration
techniques, the main objective of the proposed solver is the direct acceleration of
existing standard BEM codes, by transfering to the GPU the solver task. The CUDA
programming language is used, exploiting the particular architecture of the GPU device
for complex-valued systems. To explore the performances of the solver, two linear water
wave problems have been tested: the frequency-dependent added mass and damping
matrices of a 3D floating body, and the Helmholtz equation in a 2D domain. A NVidia
GeForce GTX 1080 graphic card has been used. The parallelized GMRES solver shows
reductions in computing times when compared with its CPU implementation.