A GPU parallel computing strategy for the material point method

Youkou Dong, Dong Wang, Mark Randolph

    Research output: Contribution to journalArticlepeer-review

    32 Citations (Scopus)


    © 2015 Elsevier Ltd. The material point method (MPM), which is a combination of the finite element and meshfree methods, suffers from significant computational workload due to the fine mesh that is required in spite of its advantages in simulating large deformations. This paper presents a parallel computing strategy for the MPM on the graphics processing unit (GPU) to boost the method's computational efficiency. The interaction between a structural element and soil is investigated to validate the applicability of the parallelisation strategy. Two techniques are developed to parallelise the interpolation from soil particles to nodes to avoid a data race; the technique that is based on workload parallelisation across threads over the nodes has a higher computational efficiency. Benchmark problems of surface footing penetration and a submarine landslide are analysed to quantify the speedup of GPU parallel computing over sequential simulations on the central processing unit. The maximum speedup with the GPU used is ~30 for single-precision calculations and decreases to ~20 for double-precision calculations.
    Original languageEnglish
    Pages (from-to)31-38
    JournalComputers and Geotechnics
    Early online date7 Feb 2015
    Publication statusPublished - May 2015


    Dive into the research topics of 'A GPU parallel computing strategy for the material point method'. Together they form a unique fingerprint.

    Cite this