Fast sparse kernel summation on Cartesian grids: An on-chip algorithm for 3D implicit surface visualization

Shengxin Zhu, Andrew J. Wathen

Research output: Chapter in Book or Report/Conference proceedingConference Proceedingpeer-review

1 Citation (Scopus)

Abstract

This paper proposes a fast algorithm for evaluating sum-mations of heterogenous sparse kernels P of the form s(x) = ΣMi=1 αiφ(ϵi∥x-xi∥) on N points on an arbitrary fine Carte-sian grid in Rd. The algorithm takes the advantage of s-parsity and the structure of Cartesian grids. The sparsity admits operations only be done in some active subsets of the Cartesian grids; the structure of Cartesian grids reduce the storage for N points from O(dN) to O(1), a constant, and thus transforms costly memory intensive operations to cheap computationally intensive operations. This results in scalable algorithm with a complexity of O(N) and makes the postprocessing of large 3D implicit surface feasible on a PC or laptop. Numerical examples for 3D surface reconstruction are presented to illustrate the efficiency of the algorithm.

Original languageEnglish
Title of host publicationHP3C 2019 - 2019 the 3rd International Conference on High Performance Compilation, Computing and Communications
PublisherAssociation for Computing Machinery
Pages20-24
Number of pages5
ISBN (Electronic)9781450366380
DOIs
Publication statusPublished - 8 Mar 2019
Event3rd International Conference on High Performance Compilation, Computing and Communications, HP3C 2019 - Xi'an, China
Duration: 8 Mar 201910 Mar 2019

Publication series

NameACM International Conference Proceeding Series

Conference

Conference3rd International Conference on High Performance Compilation, Computing and Communications, HP3C 2019
Country/TerritoryChina
CityXi'an
Period8/03/1910/03/19

Keywords

  • Kernel summations
  • Radial basis functions

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