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首页> 外文期刊>Numerical Heat Transfer, Part B. Fundamentals: An International Journal of Computation and Methodology >Highly scalable parallel computational models for large-scale RTM process modeling simulations, Part 3: Validation and performance results
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Highly scalable parallel computational models for large-scale RTM process modeling simulations, Part 3: Validation and performance results

机译:用于大规模RTM过程建模仿真的高度可扩展的并行计算模型,第3部分:验证和性能结果

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In Part 3 of this article, we illustrate the performance results and scalability obtained by implementing the traditional explicit control-volume (CV)/finite-element (FE) and a recently developed and new, implicit, pure finite-element approach in symmetric multiprocessor machines as illustrated in the preceding Part 1 and Part 2. The results indicate that the current-generation symmetric multiprocessors (SMPs) with a medium to large number of processors can be effectively used as a supercomputer (Massively Parallel Platforms, MPPs) for large-scale complex geometries in scientific and engineering problems. The recently developed and new implicit pure FE methodology is shown to be physically accurate, computationally superior, and applicable to practical large-scale problems compared to the traditional explicit CV-FE on different SMP platforms (SGI Power Challenge and SGI Origin2000). For large-scale problems, the explicit CV-FE-based modeling/analysis becomes impossible to analyze within reasonable time or realistically impossible even with parallel processing for large-scale problems. In view of such considerations, as an illustration, a large, complex finite-element mesh of 809,505 elements and 405,327 nodes has been successfully analyzed using the implicit pure FE methodology and 40 processors within a reasonable time of 4.72 hours. The proposed parallel approaches have excellent parallel efficiency and optimal scalability when compared to other relevant results in computational sciences published in the literature, with the highest degree of portability of the software code to a wide range of parallel architectures.
机译:在本文的第3部分中,我们说明了通过在对称多处理器中实现传统的显式控制量(CV)/有限元(FE)以及最近开发的新的隐式纯有限元方法而获得的性能结果和可伸缩性。结果表明,具有中等数量到大量处理器的当前对称多处理器(SMP)可以有效地用作大型计算机的超级计算机(Massively Parallel Platform,MPP)。在科学和工程问题中缩放复杂的几何图形。与在不同SMP平台(SGI Power Challenge和SGI Origin2000)上的传统显式CV-FE相比,最近开发和新的隐式纯有限元方法显示出物理上的准确性,计算上的优势,并且适用于实际的大规模问题。对于大型问题,即使在并行处理大型问题的情况下,也无法在合理的时间内进行基于CV-FE的显式基于建模/分析的分析或实际上是不可能的。考虑到这些考虑因素,例如,已经在4.72小时的合理时间内使用隐式纯有限元方法和40个处理器成功地分析了809,505个元素和405,327个节点的大型,复杂的有限元素网格。与文献中发表的计算科学中的其他相关结果相比,所提出的并行方法具有出色的并行效率和最佳可伸缩性,并且软件代码对各种并行体系结构的可移植性最高。

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