Using a Fast Multipole Method to Accelerate Spline Evaluations

Authors:
Fang Chen;David Suter
Affiliations:
-;-
Venue:
IEEE Computational Science & Engineering
Year:
1998

Citing 10
Cited 0

A fast algorithm for particle simulations

Journal of Computational Physics
A fast algorithm for the numerical evaluation of conformal mappings

SIAM Journal on Scientific and Statistical Computing
A vector spline approximation with application to meteorology

Curves and surfaces
The parallel multipole method on the connection machine

SIAM Journal on Scientific and Statistical Computing
An implementation of the fast multipole method without multipoles

SIAM Journal on Scientific and Statistical Computing
Preconditioned, adaptive, multipole-accelerated iterative methods for three-dimensional first-kind integral equations of potential theory

SIAM Journal on Scientific Computing
Grid-multipole calculations

SIAM Journal on Scientific Computing
Fast Fourier Transform Accelerated Fast Multipole Algorithm

SIAM Journal on Scientific Computing
Fast evaluation of vector splines in three dimensions

Computing
Fast Evaluation of Radial Basis Functions: Moment-Based Methods

SIAM Journal on Scientific Computing

Quantified Score

Hi-index	0.00

Visualization

Abstract

The authors consider the problem of interpolating scattered data using spline methods, presenting a general framework for using the multipole method to accelerate spline evaluations. The method depends on a tree-data structure and two hierarchical approximations: an upward multipole-expansion approximation and a downward local Taylor-series approximation. The authors also illustrate the efficiency and accuracy of the fast multipole algorithm for 2D vector spline. In comparison with the CPU time of direct calculation, which increases at a quadratic rate with the number of points, the fast algorithm achieves a higher speed in evaluation at a linear rate.