The Deflated Relaxed Incomplete Cholesky CG method for use in a real-time ship simulator
نویسندگان
چکیده
Ship simulators are used for training purposes and therefore have to calculate realistic wave patterns around the moving ship in real time. We consider a wave model that is based on the variational Boussinesq formulation, which results in a set of partial differential equations. Discretization of these equations gives a large system of linear equations, that has to be solved each time-step. The requirement of real-time simulations necessitates a fast linear solver. In this paper we study the combination of the Relaxed Incomplete Cholesky preconditioner and subdomain deflation to accelerate the Conjugate Gradient method. We show that the success of this approach depends on the relaxation parameter. For low values of the relaxation parameter, e.g. the standard IC preconditioner, the deflation method is quite successfull. This is not the case for large values of the relaxation parameter, such as the Modified IC preconditioner. We give a theoretical explanation for this difference by considering the spectrum of the preconditioned and deflated matrices. Computational results for the wave model illustrate the expected convergence behavior of the Deflated Relaxed Incomplete Cholesky CG method. We also present promising results for the combination of the deflation method and the inherently parallel block-RIC preconditioner.
منابع مشابه
A General Environment for the Treatment of Discrete Problems –
The slow convergence of the Incomplete Cholesky preconditioned Conjugate Gradient (CG) method, applied to solve the system representing a magnetostatic finite element model, is caused by the presence of a few little eigenvalues in the spectrum of the system matrix. The corresponding eigenvectors reflect large relative differences in permeability. A significant convergence improvement is achieve...
متن کاملModified Incomplete Cholesky Factorization Preconditioners for a Symmetric Positive Definite Matrix
We propose variants of the modified incomplete Cholesky factorization preconditioner for a symmetric positive definite (SPD) matrix. Spectral properties of these preconditioners are discussed, and then numerical results of the preconditioned CG (PCG) method using these preconditioners are provided to see the effectiveness of the preconditioners.
متن کاملParallel Preconditioning Techniques for Sparse CG Solvers
Conjugate gradient (CG) methods to solve sparse systems of linear equations play an important role in numerical methods for solving discretized partial diierential equations. The large size and the condition of many technical or physical applications in this area result in the need for eecient par-allelization and preconditioning techniques of the CG method. In particular for very ill-condition...
متن کاملRobust and Eecient Computation of Optical Flow 1 List of Figures
1 The discrepancy between the gradient directions of the function I 0 and I 1 at the i-th location is small and thus the use of the gradient direction as the search direction for the i-th component is robust; while the the j-th component of the gradient direction is unreliable for a local 2 Frames from the (a) Square 2 and (b) Diverging Tree image sequences. 19 3 Computed optical ow of the (a) ...
متن کاملAccelerating the Conjugate Gradient Algorithm with GPUs in CFD Simulations
This paper illustrates how GPU computing can be used to accelerate computational fluid dynamics (CFD) simulations. For sparse linear systems arising from finite volume discretization, we evaluate and optimize the performance of Conjugate Gradient (CG) routines designed for manycore accelerators and compare against an industrial CPU-based implementation. We also investigate how the recent advanc...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2010