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| Parallel implement of large-scale linear elastic FEM in cloud computing environment |
| Received:December 20, 2015 Revised:April 25, 2016 |
| View Full Text View/Add Comment Download reader |
| DOI：10.7511/jslx201702011 |
| KeyWord:cloud computing Spark RDDs linear finite element method spatial truss systems parallel computing |
| Author | Institution |
| 林海铭 |
华中科技大学 力学系 武汉 ;广东省建筑科学研究院集团股份有限公司 广州 |
| 刘小虎 |
华中科技大学 力学系 武汉 |
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| Abstract: |
| Considering the fact that iterative algorithm cannot be realized efficiently on Hadoop MapReduce platform, this paper proposed a large-scale finite-element parallel algorithm based on the Resilient Distributed Datasets on the Spark platform in order to explore how to implement iterative algorithm efficiently. The proposed algorithm was then verified using the space truss model on a 6-node Hadoop+Spark platform. Comparisons were made between a performance of Spark-based algorithms and Hadoop-based algorithms of linear elastic FEM. The results indicate that the number of the DOFs of the space truss problem that can be solved by the Spark-based parallel algorithm may reach 15000000, which is much more than that solved by the Hadoop-based parallel algorithm. Obviously, the Spark-based parallel algorithm is preferable. Moreover, the proposed algorithm exhibits an enhanced computing efficiency compared with the Hadoop-based parallel algorithm. Specifically, for a small-scale space truss model, the speed-up ratio reaches 200 while for a large-scale space truss model, it is approximately 7 or 8. |