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arXiv 1601.02245math.NAcs.DCcs.NA
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关于常微分方程并行求解

On parallel solution of ordinary differential equations

Purdue University(普渡大学);Facultad de Ciencias, Universidad de Colima(科利马大学理学院)

Alejandra Gaitán Montejo, Octavio A. Michel-Manzo, César A. Terrero-Escalante

AI总结:

本文比较了并行迭代龙格-库塔方法与串行四阶龙格-库塔和 Dormand-Prince 方法的性能,提出了一种全并行化算法以估算最佳步长,该方法在处理大规模系统时表现更优。

摘要:

本文比较了并行迭代龙格-库塔方法与串行四阶龙格-库塔和 Dormand-Prince 方法的性能。发现并行方法的运行时间与串行版本相当,但消耗更多计算资源。提出了一种全并行化算法以估算最佳步长,证明该方法在处理非常大规模系统时表现更优。

英文摘要:

In this paper the performance of a parallel iterated Runge-Kutta method is compared versus those of the serial fouth order Runge-Kutta and Dormand-Prince methods. It was found that, typically, the runtime for the parallel method is comparable to that of the serial versions, thought it uses considerably more computational resources. A new algorithm is proposed where full parallelization is used to estimate the best stepsize for integration. It is shown that this new method outperforms the others, notably, in the integration of very large systems.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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