315 research outputs found
Multidomain Spectral Method for the Helically Reduced Wave Equation
We consider the 2+1 and 3+1 scalar wave equations reduced via a helical
Killing field, respectively referred to as the 2-dimensional and 3-dimensional
helically reduced wave equation (HRWE). The HRWE serves as the fundamental
model for the mixed-type PDE arising in the periodic standing wave (PSW)
approximation to binary inspiral. We present a method for solving the equation
based on domain decomposition and spectral approximation. Beyond describing
such a numerical method for solving strictly linear HRWE, we also present
results for a nonlinear scalar model of binary inspiral. The PSW approximation
has already been theoretically and numerically studied in the context of the
post-Minkowskian gravitational field, with numerical simulations carried out
via the "eigenspectral method." Despite its name, the eigenspectral technique
does feature a finite-difference component, and is lower-order accurate. We
intend to apply the numerical method described here to the theoretically
well-developed post-Minkowski PSW formalism with the twin goals of spectral
accuracy and the coordinate flexibility afforded by global spectral
interpolation.Comment: 57 pages, 11 figures, uses elsart.cls. Final version includes
revisions based on referee reports and has two extra figure
A direct solver with O(N) complexity for variable coefficient elliptic PDEs discretized via a high-order composite spectral collocation method
A numerical method for solving elliptic PDEs with variable coefficients on
two-dimensional domains is presented. The method is based on high-order
composite spectral approximations and is designed for problems with smooth
solutions. The resulting system of linear equations is solved using a direct
(as opposed to iterative) solver that has optimal O(N) complexity for all
stages of the computation when applied to problems with non-oscillatory
solutions such as the Laplace and the Stokes equations. Numerical examples
demonstrate that the scheme is capable of computing solutions with relative
accuracy of or better, even for challenging problems such as highly
oscillatory Helmholtz problems and convection-dominated convection diffusion
equations. In terms of speed, it is demonstrated that a problem with a
non-oscillatory solution that was discretized using nodes was solved
in 115 minutes on a personal work-station with two quad-core 3.3GHz CPUs. Since
the solver is direct, and the "solution operator" fits in RAM, any solves
beyond the first are very fast. In the example with unknowns, solves
require only 30 seconds.Comment: arXiv admin note: text overlap with arXiv:1302.599
SlabLU: A Two-Level Sparse Direct Solver for Elliptic PDEs
The paper describes a sparse direct solver for the linear systems that arise
from the discretization of an elliptic PDE on a two dimensional domain. The
solver is designed to reduce communication costs and perform well on GPUs; it
uses a two-level framework, which is easier to implement and optimize than
traditional multi-frontal schemes based on hierarchical nested dissection
orderings. The scheme decomposes the domain into thin subdomains, or "slabs".
Within each slab, a local factorization is executed that exploits the geometry
of the local domain. A global factorization is then obtained through the LU
factorization of a block-tridiagonal reduced coefficient matrix. The solver has
complexity for the factorization step, and for each
solve once the factorization is completed.
The solver described is compatible with a range of different local
discretizations, and numerical experiments demonstrate its performance for
regular discretizations of rectangular and curved geometries. The technique
becomes particularly efficient when combined with very high-order convergent
multi-domain spectral collocation schemes. With this discretization, a
Helmholtz problem on a domain of size (for
which N=100 \mbox{M}) is solved in 15 minutes to 6 correct digits on a
high-powered desktop with GPU acceleration
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