有限元负载平衡框架的调优

M. Bošanský, B. Patzák
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引用次数: 2

摘要

即使在最新的硬件上,许多工程问题也很难解决。这些问题在并行计算机上的数值解可以通过并行执行选定的任务来显著减少计算时间。本文研究了基于分布式内存模型领域分解范式的有限元软件并行负载均衡框架的优化。本文描述了确定实际权重的技术,比较了各个处理单元的计算性能。这些权重是网格(重新)划分的基本输入,必须在模拟开始时和负载不平衡明显时执行。在基准问题上对所提技术的能力和性能进行了评估和讨论。摘要:即使在最新的硬件上,许多工程问题的解决也非常困难。这些问题在并行计算机上的数值解可以通过并行执行选定的任务来显著减少计算时间。本文研究了基于分布式内存模型领域分解范式的有限元软件并行负载均衡框架的优化。本文描述了确定实际权重的技术,比较了各个处理单元的计算性能。这些权重是网格(重新)划分的基本输入,必须在模拟开始时和负载不平衡明显时执行。在基准问题上对所提技术的能力和性能进行了评估和讨论。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
ON TUNING OF FINITE ELEMENT LOAD BALANCING FRAMEWORK
: Many engineering problems are extremely demanding to solve even on recent hardware. Numerical solutions of these problems on parallel computers can significantly reduce computational time by performing selected tasks concurrently. This paper deals with tuning up the parallel load balancing framework of the finite element software, which is based on domain decomposition paradigm for distributed memory model. The paper describes the technique to determine the actual weights comparing computational performance of individual processing units. These weights are fundamental inputs for mesh (re)partitioning that has to be performed at the beginning of the simulation and whenever the load imbalance is significant. The capabilities and performance of the proposed technique are evaluated on the benchmark problem and discussed. Abstract: Many engineering problems are extremely demanding to solve even on recent hardware. Numerical solutions of these problems on parallel computers can significantly reduce computational time by performing selected tasks concurrently. This paper deals with tuning up the parallel load balancing framework of the finite element software, which is based on domain decomposition paradigm for distributed memory model. The paper describes the technique to determine the actual weights comparing computational performance of individual processing units. These weights are fundamental inputs for mesh (re)partitioning that has to be performed at the beginning of the simulation and whenever the load imbalance is significant. The capabilities and performance of the proposed technique are evaluated on the benchmark problem and discussed.
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