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    Application of Assembly of Finite Element Methods on Graphics Processors for Real-Time Elastodynamics

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    Type
    Book Chapter
    Authors
    Cecka, Cris
    Lew, Adrian
    Darve, Eric
    Date
    2012
    Permanent link to this record
    http://hdl.handle.net/10754/597594
    
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    Abstract
    This chapter discusses multiple strategies to perform general computations on unstructured grids, with specific application to the assembly of matrices in finite element methods (FEMs). It reviews and applies two methods for assembly of FEMs to produce and accelerate a FEM model for a nonlinear hyperelastic solid where the assembly, solution, update, and visualization stages are performed solely on the GPU, benefiting from speed-ups in each stage and avoiding costly GPUCPU transfers of data. For each method, the chapter discusses the NVIDIA GPU hardware's limiting resources, optimizations, key data structures, and dependence of the performance with respect to problem size, element size, and GPU hardware generation. Furthermore, this chapter informs potential users of the benefits of GPU technology, provides guidelines to help them implement their own FEM solutions, gives potential speed-ups that can be expected, and provides source code for reference. © 2012 Elsevier Inc. All rights reserved.
    Citation
    Cecka C, Lew A, Darve E (2012) Application of Assembly of Finite Element Methods on Graphics Processors for Real-Time Elastodynamics. GPU Computing Gems Jade Edition: 187–205. Available: http://dx.doi.org/10.1016/b978-0-12-385963-1.00016-2.
    Sponsors
    This work was partially supported by a research grant from the Academic Excellence Alliance program between King Abdullah University of Science and Technology and Stanford University. We also thank the Army High-Performance Computing and Research Center (AHPCRC) at Stanford for its support, as well as Juan-Pablo Samper-Mejia and Vivian Nguyen for their contribution during the 2010 AHPCRC Summer Institute.
    Publisher
    Elsevier BV
    Journal
    GPU Computing Gems Jade Edition
    DOI
    10.1016/b978-0-12-385963-1.00016-2
    ae974a485f413a2113503eed53cd6c53
    10.1016/b978-0-12-385963-1.00016-2
    Scopus Count
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