Applications of A Hyper–Graph Grammar System in Adaptive Finite–Element Computations

Author:

Gurgul Piotr1,Jopek Konrad2,Pingali Keshav3,Paszyńska Anna4

Affiliation:

1. Dropbox Inc., 333 Brannan Street, San Francisco , USA

2. Department of Computer Science AGH University of Science and Technology, al. Mickiewicza 30, Krakόw , Poland

3. Institute for Computational and Engineering Sciences The University of Texas at Austin, Austin , USA

4. Faculty of Physics, Astronomy and Applied Computer Science Jagiellonian University, ul. Łojasiewicza 11, Krakόw , Poland

Abstract

Abstract This paper describes application of a hyper-graph grammar system for modeling a three-dimensional adaptive finite element method. The hyper-graph grammar approach allows obtaining a linear computational cost of adaptive mesh transformations and computations performed over refined meshes. The computations are done by a hyper-graph grammar driven algorithm applicable to three-dimensional problems. For the case of typical refinements performed towards a point or an edge, the algorithm yields linear computational cost with respect to the mesh nodes for its sequential execution and logarithmic cost for its parallel execution. Such hyper-graph grammar productions are the mathematical formalism used to describe the computational algorithm implementing the finite element method. Each production indicates the smallest atomic task that can be executed concurrently. The mesh transformations and computations by using the hyper-graph grammar-based approach have been tested in the GALOIS environment. We conclude the paper with some numerical results performed on a shared-memory Linux cluster node, for the case of three-dimensional computational meshes refined towards a point, an edge and a face.

Publisher

Walter de Gruyter GmbH

Subject

Applied Mathematics,Engineering (miscellaneous),Computer Science (miscellaneous)

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Hypergraph Grammar-Based Model of Adaptive Bitmap Compression;Lecture Notes in Computer Science;2020

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