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Fourier Analysis of Inexact Parallel Block Jacobi with Source Iteration Preconditioning and Computational Experimentation with Parallel Block Jacobi / Source Iteration Hybrid Methods

机译:与平行块XACOBI /源迭代混合方法源迭代预处理和计算实验的傅立叶分析

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Parallel Block Jacobi (PBJ) iterative methods used in transport calculations experienceiterative slowdown in problems with optically thin spatial cells due to asynchronicity.Previously we tested hybrid methods which execute both Parallel Block Jacobi – IntegralTransport Matrix Method (PBJ-ITMM) and Source Iterations (SI) interchangeably and foundthis to effectively accelerate PBJ-ITMM. This acceleration was conjectured to be a result ofthe most prevalent phenomena in optically thin and thick cells being streaming and collision,respectively, with SI able to model the streaming and PBJ-ITMM able to resolve localcollisions. In this work, we support this claim and further investigate its implications byperforming Fourier analysis on Inexact Parallel Block Jacobi (IPBJ) executed in series withSI. Our analysis establishes that lagging the scattering source in IPBJ causes the spectral radiusof the P-IP-SI method (IPBJ preconditioned with SI) to asymptote to c~2 with increasing celloptical thickness, where c is the scattering ratio, far exceeding the spectral radius of P-PI-SI(PBJ-ITMM preconditioned with SI) in thick cells. Upon theoretically demonstrating theadvantage of using P-PI-SI over P-IP-SI, we perform computational experiments on bothmethods. These experiments show that asynchronous combination of PBJ-ITMM and SI (AHPI-SI) is the most effective PBJ / SI hybrid method among considered options.
机译:平行块Jacobi(PBJ)迭代方法用于运输计算经验由于异步,光学薄空间细胞问题的迭代放缓。以前我们测试了执行两个平行块Jacobi - 积分的混合方法传输矩阵方法(PBJ-ITMM)和源迭代(SI)互换,发现这是有效加速PBJ-ITMM。劝告这种加速度是光学薄和厚细胞中最普遍的现象是流媒体和碰撞,分别使用SI能够模拟流和PBJ-ITMM能够解析本地碰撞。在这项工作中,我们支持这一索赔,并进一步调查其含义对与串联执行的不精确并行块Jacobi(IPBJ)进行傅立叶分析Si。我们的分析建立了IPBJ中的散射源导致光谱半径与增加细胞的P-IP-SI方法(用Si预处理到Si)到渐近C〜2光学厚度,其中C是散射比,远远超过p-pi-si的光谱半径(PBJ-ITMM在厚细胞中预处理)。在理论上展示使用P-PI-SI在P-IP-SI上使用P-PI-SI的优点,我们对两者进行计算实验方法。这些实验表明,PBJ-ITMM和Si的异步组合(AHPI-SI)是考虑选项中最有效的PBJ / SI混合方法。

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