High-performance hybrid CPU and GPU parallel algorithm for digital volume correlation

Mark Gates, Michael T. Heath, John Lambros

Research output: Contribution to journalArticlepeer-review

Abstract

We present a hybrid Message Passing Interface (MPI) and graphics processing unit (GPU)-based parallel digital volume correlation (DVC) algorithm for measuring three-dimensional (3D) displacement and strain fields inside a material undergoing motion or deformation. Our algorithm achieves resolution comparable to that achieved in two-dimensional (2D) digital image correlation (DIC), in time that is commensurate with the image acquisition time, in this case, using microcomputed tomography (μ CT) for scanning images. For DVC, the volume of data and number of correlation points both grow cubically with the linear dimensions of the image. We turn to parallel computing to gain sufficient processing power to scale to high resolution, and are able to achieve more than an order-of-magnitude increase in resolution compared with previous efforts that are not based on a parallel framework.

Original languageEnglish (US)
Pages (from-to)92-106
Number of pages15
JournalInternational Journal of High Performance Computing Applications
Volume29
Issue number1
DOIs
StatePublished - Feb 13 2015

Keywords

  • GPU computing
  • X-ray tomography
  • digital volume correlation
  • image registration
  • parallel computing
  • strain measurement

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Hardware and Architecture

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