A GPU-based caching strategy for multi-material linear elastic FEM on regular grids

PLoS One. 2020 Oct 30;15(10):e0240813. doi: 10.1371/journal.pone.0240813. eCollection 2020.

Abstract

In this study, we present a novel strategy to the method of finite elements (FEM) of linear elastic problems of very high resolution on graphic processing units (GPU). The approach exploits regularities in the system matrix that occur in regular hexahedral grids to achieve cache-friendly matrix-free FEM. The node-by-node method lies in the class of block-iterative Gauss-Seidel multigrid solvers. Our method significantly improves convergence times in cases where an ordered distribution of distinct materials is present in the dataset. The method was evaluated on three real world datasets: An aluminum-silicon (AlSi) alloy and a dual phase steel material sample, both captured by scanning electron tomography, and a clinical computed tomography (CT) scan of a tibia. The caching scheme leads to a speed-up factor of ×2-×4 compared to the same code without the caching scheme. Additionally, it facilitates the computation of high-resolution problems that cannot be computed otherwise due to memory consumption.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Computer Graphics
  • Computer Systems
  • Finite Element Analysis / statistics & numerical data*
  • Humans
  • Image Processing, Computer-Assisted / methods*
  • Software
  • Tomography, X-Ray Computed / methods

Grants and funding

T.D., C.S., P.S. The authors gratefully acknowledge the financial support of the German Bundesministerium für Bildung und Forschung (BMBF) under the grant 13GW0124. https://www.bmbf.de/ The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.