4,809 research outputs found
Fast and Efficient Numerical Methods for an Extended Black-Scholes Model
An efficient linear solver plays an important role while solving partial
differential equations (PDEs) and partial integro-differential equations
(PIDEs) type mathematical models. In most cases, the efficiency depends on the
stability and accuracy of the numerical scheme considered. In this article we
consider a PIDE that arises in option pricing theory (financial problems) as
well as in various scientific modeling and deal with two different topics. In
the first part of the article, we study several iterative techniques
(preconditioned) for the PIDE model. A wavelet basis and a Fourier sine basis
have been used to design various preconditioners to improve the convergence
criteria of iterative solvers. We implement a multigrid (MG) iterative method.
In fact, we approximate the problem using a finite difference scheme, then
implement a few preconditioned Krylov subspace methods as well as a MG method
to speed up the computation. Then, in the second part in this study, we analyze
the stability and the accuracy of two different one step schemes to approximate
the model.Comment: 29 pages; 10 figure
Analysis of Iterative Methods for the Steady and Unsteady Stokes Problem: Application to Spectral Element Discretizations
A new and detailed analysis of the basic Uzawa algorithm for decoupling of the pressure and the velocity in the steady and unsteady Stokes operator is presented. The paper focuses on the following new aspects: explicit construction of the Uzawa pressure-operator spectrum for a semiperiodic model problem; general relationship of the convergence rate of the Uzawa procedure to classical inf-sup discretization analysis; and application of the method to high-order variational discretization
A Robust Solver for a Second Order Mixed Finite Element Method for the Cahn-Hilliard Equation
We develop a robust solver for a second order mixed finite element splitting
scheme for the Cahn-Hilliard equation. This work is an extension of our
previous work in which we developed a robust solver for a first order mixed
finite element splitting scheme for the Cahn-Hilliard equaion. The key
ingredient of the solver is a preconditioned minimal residual algorithm (with a
multigrid preconditioner) whose performance is independent of the spacial mesh
size and the time step size for a given interfacial width parameter. The
dependence on the interfacial width parameter is also mild.Comment: 17 pages, 3 figures, 4 tables. arXiv admin note: substantial text
overlap with arXiv:1709.0400
Multiple Right-Hand Side Techniques in Semi-Explicit Time Integration Methods for Transient Eddy Current Problems
The spatially discretized magnetic vector potential formulation of
magnetoquasistatic field problems is transformed from an infinitely stiff
differential algebraic equation system into a finitely stiff ordinary
differential equation (ODE) system by application of a generalized Schur
complement for nonconducting parts. The ODE can be integrated in time using
explicit time integration schemes, e.g. the explicit Euler method. This
requires the repeated evaluation of a pseudo-inverse of the discrete curl-curl
matrix in nonconducting material by the preconditioned conjugate gradient (PCG)
method which forms a multiple right-hand side problem. The subspace projection
extrapolation method and proper orthogonal decomposition are compared for the
computation of suitable start vectors in each time step for the PCG method
which reduce the number of iterations and the overall computational costs.Comment: 4 pages, 5 figure
Matrix-free GPU implementation of a preconditioned conjugate gradient solver for anisotropic elliptic PDEs
Many problems in geophysical and atmospheric modelling require the fast
solution of elliptic partial differential equations (PDEs) in "flat" three
dimensional geometries. In particular, an anisotropic elliptic PDE for the
pressure correction has to be solved at every time step in the dynamical core
of many numerical weather prediction models, and equations of a very similar
structure arise in global ocean models, subsurface flow simulations and gas and
oil reservoir modelling. The elliptic solve is often the bottleneck of the
forecast, and an algorithmically optimal method has to be used and implemented
efficiently. Graphics Processing Units have been shown to be highly efficient
for a wide range of applications in scientific computing, and recently
iterative solvers have been parallelised on these architectures. We describe
the GPU implementation and optimisation of a Preconditioned Conjugate Gradient
(PCG) algorithm for the solution of a three dimensional anisotropic elliptic
PDE for the pressure correction in NWP. Our implementation exploits the strong
vertical anisotropy of the elliptic operator in the construction of a suitable
preconditioner. As the algorithm is memory bound, performance can be improved
significantly by reducing the amount of global memory access. We achieve this
by using a matrix-free implementation which does not require explicit storage
of the matrix and instead recalculates the local stencil. Global memory access
can also be reduced by rewriting the algorithm using loop fusion and we show
that this further reduces the runtime on the GPU. We demonstrate the
performance of our matrix-free GPU code by comparing it to a sequential CPU
implementation and to a matrix-explicit GPU code which uses existing libraries.
The absolute performance of the algorithm for different problem sizes is
quantified in terms of floating point throughput and global memory bandwidth.Comment: 18 pages, 7 figure
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