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ASYNCHRONOUS PARAREAL TIME DISCRETIZATION FOR PARTIAL DIFFERENTIAL EQUATIONS

机译:偏微分方程的异步距离时间离散化

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Asynchronous iterations have been investigated more and more for both scaling and fault-resilience purposes on high performance computing platforms. While so far, they have been exclusively applied within space domain decomposition frameworks, this paper advocates a novel application direction targeting time-decomposed time-parallel approaches. Specifically, an asynchronous iterative model is derived from the Parareal scheme, for which convergence and speedup analysis are then conducted. It turned out that Parareal and async-Parareal feature very close convergence conditions, asymptotically equivalent, including the finite-time termination property. Based on a computational cost model aware of unsteady communication delays, our speedup analysis shows the potential performance gain from asynchronous iterations, which is confirmed by some experimental cases of heat evolution on a homogeneous supercomputer. This primary work clearly suggests possible further benefits from asynchronous iterations.
机译:对于高性能计算平台的缩放和故障恢复性来说,越来越多地研究了异步迭代。虽然到目前为止,但它们被专门应用于空间域分解框架,而本文提倡一种针对时间分解的时间平行方法的新应用方向。具体地,来自偏射线方案的异步迭代模型,然后进行收敛和加速分析。事实证明,子叶片和异步 - 宫间隙具有非常紧密的收敛条件,渐近的等价物,包括有限时间终端性质。基于意识到不稳定的通信延迟的计算成本模型,我们的加速分析显示了异步迭代的潜在性能增益,这是由均匀超级计算机上的一些实验情况确认的热量进化的实验情况。此主要工作明确表明异步迭代可能的进一步优势。

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