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A space-time parallel algorithm with adaptive mesh refinement for computational fluid dynamics

机译:具有计算流体动力学的自适应网格细化的时空并行算法

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This paper describes a space-time parallel algorithm with space-time adaptivemesh refinement (AMR).AMRwith subcycling is added to multigrid reduction-in-time (MGRIT) in order to provide solution efficient adaptive grids with a reduction in work performed on coarser grids. This algorithm is achieved by integrating two software libraries: XBraid and Chombo (Chombo software package for AMR applications-design document, 2014). The former is a parallel time integration library using multigrid and the latter is a massively parallel structuredAMRlibrary. Employing this adaptive space-time parallel algorithm is Chord (Comput Fluids 123:202–217, 2015), a computational fluid dynamics (CFD) application code for solving compressible fluid dynamics problems. For the same solution accuracy, speedups are demonstrated from the use of space-time parallelization over the time-sequential integration on Couette flow and Stokes’ second problem. On a transient Couette flow case, at least a 1.5× speedup is achieved, and with a time periodic problem, a speedup of up to 13.7× over the time-sequential case is obtained. In both cases, the speedup is achieved by adding processors and exploring additional parallelization in time. The numerical experiments show the algorithm is promising for CFD applications that can take advantage of the time parallelism. Future work will focus on improving the parallel performance and providing more tests with complex fluid dynamics to demonstrate the full potential of the algorithm.
机译:本文介绍了一种时空并行算法,具有时空调整内容细化(AMR).Amrwith子单循环被添加到多重线减少时间(MGRIT),以便提供解决方案高效的自适应网格,其在较粗糙网格上执行的工作减少。通过集成两个软件库来实现该算法:XBRAID和Chombo(AMR应用程序的Chombo软件包 - 2014年的Chombo软件包)。前者是使用Multigrid的并行时间集成库,后者是一种大规模并行结构的结构ullibrary。采用这种自适应时空并行算法是弦(计算流体123:202-217,2015),用于解决可压缩流体动力学问题的计算流体动力学(CFD)应用程序代码。出于相同的解决方案准确性,通过在Coute流程和Stokes的第二个问题上使用时空并行化使用时空并行化的加速。在瞬态耦合流量外壳上,实现至少1.5倍加速,并且随着时间的周期性问题,获得在时间顺序情况下的高达13.7倍的加速。在这两种情况下,通过添加处理器并及时探索额外的并行化来实现加速度。数值实验表明,该算法对CFD应用有前途,可以利用时间并行性。未来的工作将专注于改善并行性能并提供更多的测试,并提供复杂的流体动力学来证明算法的全部潜力。

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