首页> 外文期刊>International journal of parallel programming >A Parallel Approach for the Generation of Unstructured Meshes with Billions of Elements on Distributed-Memory Supercomputers
【24h】

A Parallel Approach for the Generation of Unstructured Meshes with Billions of Elements on Distributed-Memory Supercomputers

机译:分布式内存超级计算机上具有数十亿个元素的非结构化网格生成的并行方法

获取原文
获取原文并翻译 | 示例

摘要

This paper describes a parallel approach for the rapid generation of ultra-large-scale unstructured meshes on distributed-memory supercomputers. A medium-sized initial mesh is prepared first. Afterwards, a two-level domain decomposition (DD) strategy is used to split and distribute the initial mesh to different cores. Finally, the parallel mesh generation, comprising a recursive procedure which includes parallel surface recovery, parallel boundary updating, and parallel mesh multiplication, is performed. The two-level DD differentiates the intra-node and inter-node communication to reduce communication overheads. A global indexing and updating scheme is used to make the mesh multiplication devoid of communication. A new parallel surface recovery algorithm without communication is developed to maintain the fidelity of the resulting mesh model to the original geometric model. Tests of the parallel approach for some real-life problems on supercomputers (Dawning-5000A and Tianhe-2) are presented. Issues regarding the speedup, parallel efficiency, and mesh quality are discussed. Results show that the proposed parallel approach has a reasonably good scalability, that the quality of the resulting mesh is improved, and that ultra-large-scale meshes with billions of elements can be generated quickly.
机译:本文介绍了一种在分布式内存超级计算机上快速生成超大型非结构化网格的并行方法。首先准备一个中等大小的初始网格。之后,使用两级域分解(DD)策略将初始网格划分并分配到不同的核心。最后,执行并行网格生成,包括递归过程,该过程包括并行曲面恢复,并行边界更新和并行网格乘法。二级DD区分节点内和节点间通信,以减少通信开销。全局索引和更新方案用于使网状乘法没有通信。开发了一种无需通信的新的平行曲面恢复算法,以保持所得网格模型相对于原始几何模型的保真度。提出了在超级计算机(Dawning-5000A和Tianhe-2)上一些实际问题的并行方法测试。讨论了有关加速,并行效率和网格质量的问题。结果表明,所提出的并行方法具有相当好的可扩展性,改进了所得网格的质量,并且可以快速生成具有数十亿个元素的超大型网格。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号