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Prioritized Multiplicative Schwarz Procedures for Solving Linear Systems

机译:用于解决线性系统的优先级乘法施瓦茨程序

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We describe a new algorithm designed to quickly and robustly solve general linear problems of the form Ax = b. We describe both serial and parallel versions of the algorithm, which can be considered a prioritized version of an Alternating Multiplicative Schwarz procedure. We also adopt a general view of alternating Multiplicative Schwarz procedures which motivates their use on arbitrary problems (even which may not have arisen from problems that are naturally decomposable) by demonstrating that, even in a serial context, algorithms should use many, many partitions to accelerate convergence; having such an over-partitioned system also allows easy parallelization of the algorithm, and scales extremely well. We present extensive empirical evidence which demonstrates that our algorithm, with a companion subsolver, can often improve performance by several orders of magnitude over the subsolver by itself and over other algorithms.
机译:我们描述了一种旨在快速且鲁棒地解决形式轴= B的一般线性问题的新算法。我们描述了算法的串行和并行版本,可以被视为交替乘法施瓦茨过程的优先级版本。我们还采用了交替的乘法施瓦茨程序的一般性观点,它通过证明即使在串行上下文中,即使在串行上下文中,算法应该使用许多分区,即使是自然可分解的问题也可能没有出现的问题。加速收敛;具有这样的过分区系统还允许算法容易地并行化,并且非常稳定。我们展示了广泛的经验证据,表明我们的算法与伴侣子相机一起可以通过自身和其他算法通过对象的几个数量级来提高性能。

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