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A new row-wise parallel finite element analysis algorithm (RWPFEA) with dynamic load balancing.

机译：具有动态负载平衡的新的行式并行有限元分析算法（RWPFEA）。

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摘要

This research is concerned with the parallel finite element analysis (PFEA) of structures. For structural engineering problems, parallelization has been typically accomplished by one, or possibly a combination of three types of algorithms; namely: node-wise algorithms, element-wise algorithms, and domain-wise algorithms. These algorithms focus on partitioning schemes that optimize one of the solution steps in PFEA, while the other steps are parallelized without optimization, or not parallelized at all. In this work, a parallel scheme is devised that efficiently parallelizes all steps of PFEA.; This work introduces a new approach that considers the four steps of nonlinear finite element analysis. (i) element state determination, (ii) assembly, (iii) application of boundary conditions, and (iv) solution of the governing system of equations, as computational units. A computational unit has processing, storage, and communication requirements. It can be partitioned into blocks of rows. Each block of rows in these processing units is contained within a separate computing processor. Using this paradigm, a procedure is devised that minimizes inter-processor communication, reduces data redundancy, and balances computational workload among processor by migrating rows from one block to another. The new Row-Wise PFEA (RWPFEA) algorithm is based on a row-wise matrix distribution. Thus, it is capable of exploiting the nature of distributed compressed row sparse (CRS) matrices and multivectors to improve concurrency.; As part of this research a new dynamic load balancing (DLB) technique has also been devised. The DLB technique has been designed specifically to balance the computational workload among processors most suited for nonlinear analysis of structures.; This new algorithm has been implemented in ParaStruc, a parallel structural analysis system, which has been built on Trilinos, a set of parallel numerical libraries developed by researchers in the Sandia National Laboratory. ParaStruc is a lightweight fully parallelized PFEA system, which contains only two classes, a preprocessor, a postprocessor, and a math library. Preliminary studies have shown this to be a promising approach, since superior performance advantage in terms of speedup, efficiency, and isoefficiency has been achieved in the nonlinear analysis of structures under static and dynamic response. The performance and efficiency of this algorithm has been verified with numerical simulations of a high-rise 3-D building structure. The results of ParaStruc have been compared with those obtained using the ABAQUS, which is a leading commercial finite element analysis software with parallel processing and dynamic load balancing capabilities. Finally, the performance of the proposed parallel system is studied for two types of parallel architectures, namely, shared memory and distributed memory systems. It is found that its performance is excellent in both architectures. However, in general, the performance in the distributed memory system is superior to that in the shared memory system. This is because the additional local memory inherent to these systems positively affects the performance of the memory-dependent state determination step, which is the most time consuming step in the analysis.
机译：这项研究与结构的平行有限元分析（PFEA）有关。对于结构工程问题，并行化通常是通过一种算法或三种算法的组合来完成的。即：节点算法，元素算法和域算法。这些算法专注于分区方案，这些方案优化了PFEA中的一个解决步骤，而其他步骤则未经优化而并行化，或者根本不并行化。在这项工作中，设计了一种并行方案，可以有效地并行化PFEA的所有步骤。这项工作引入了一种新方法，该方法考虑了非线性有限元分析的四个步骤。 （i）元素状态确定；（ii）组装；（iii）边界条件的应用；以及（iv）方程式控制系统的解，作为计算单位。计算单元具​​有处理，存储和通信要求。可以将其划分为行块。这些处理单元中的每个行块都包含在单独的计算处理器中。通过使用这种范例，设计了一种过程，该过程通过将行从一个块迁移到另一个块来最小化处理器之间的通信，减少数据冗余并平衡处理器之间的计算工作量。新的行明智PFEA（RWPFEA）算法基于行矩阵分布。因此，它能够利用分布式压缩行稀疏（CRS）矩阵和多矢量的性质来提高并发性。作为这项研究的一部分，还设计了一种新的动态负载平衡（DLB）技术。 DLB技术经过专门设计，可以平衡最适合结构非线性分析的处理器之间的计算工作量。这种新算法已在ParaStruc（一种平行结构分析系统）中实现，该系统基于Trilinos构建，Trilinos是由Sandia国家实验室的研究人员开发的一组并行数值库。 ParaStruc是一个轻量级的完全并行化PFEA系统，它仅包含两个类：预处理器，后处理器和数学库。初步研究表明这是一种有前途的方法，因为在静态和动态响应下的结构非线性分析中，在加速，效率和等效率方面均具有卓越的性能优势。该算法的性能和效率已通过高层3-D建筑结构的数值模拟得到了验证。将ParaStruc的结果与使用ABAQUS获得的结果进行了比较，ABAQUS是具有并行处理和动态负载平衡功能的领先商业有限元分析软件。最后，针对两种类型的并行体系结构，即共享内存和分布式内存系统，研究了所提出的并行系统的性能。发现在两种体系结构中其性能都非常好。但是，通常，分布式存储系统中的性能要优于共享存储系统中的性能。这是因为这些系统固有的附加本地内存会对内存相关状态确定步骤的性能产生积极影响，而内存状态确定步骤是分析中最耗时的步骤。

著录项

  • 作者

    Al-Sayegh, Ammar Taher.;

  • 作者单位

    Purdue University.$bCivil Engineering.;

  • 授予单位 Purdue University.$bCivil Engineering.;
  • 学科 Engineering Civil.; Computer Science.
  • 学位 Ph.D.
  • 年度 2007
  • 页码 162 p.
  • 总页数 162
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 建筑科学;自动化技术、计算机技术;
  • 关键词

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