An Efficient and Fast Sparse Grid Algorithm for High-Dimensional Numerical Integration

• Published in: Mathematics (Basel) Vol. 11; no. 19; p. 4191
• Main Authors: Zhong, Huicong, Feng, Xiaobing
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.10.2023
• Subjects: Algorithms; curse of dimensionality; Efficiency; Grid method; high-dimensional integration; Image processing; Integrals; Iterative methods; Mathematical analysis; Methods; multilevel dimension iteration (MDI); Numerical analysis; Numerical integration; numerical quadrature rules; Polynomials; sparse grid (SG) method
• ISSN: 2227-7390; 2227-7390
• DOI: 10.3390/math11194191

This paper is concerned with developing an efficient numerical algorithm for the fast implementation of the sparse grid method for computing the d-dimensional integral of a given function. The new algorithm, called the MDI-SG (multilevel dimension iteration sparse grid) method, implements the sparse grid method based on a dimension iteration/reduction procedure. It does not need to store the integration points, nor does it compute the function values independently at each integration point; instead, it reuses the computation for function evaluations as much as possible by performing the function evaluations at all integration points in a cluster and iteratively along coordinate directions. It is shown numerically that the computational complexity (in terms of CPU time) of the proposed MDI-SG method is of polynomial order O(d3Nb)(b≤2) or better, compared to the exponential order O(N(logN)d−1) for the standard sparse grid method, where N denotes the maximum number of integration points in each coordinate direction. As a result, the proposed MDI-SG method effectively circumvents the curse of dimensionality suffered by the standard sparse grid method for high-dimensional numerical integration.