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A speed-up algorithm in Monte Carlo simulation for fault tree analysis with GPU computing

机译:蒙特卡洛仿真中的加速算法,用于通过GPU计算进行故障树分析

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The reliability analysis of critical systems could be performed with fault tree analysis. One of the approaches used for fault tree analysis is Monte Carlo simulation. The purpose of this paper is therefore to show an algorithm to speed-up Monte Carlo simulation for analyzing fault tree with parallel computing in GPU. To this end, we use time-to-failure tree to model fault tree with Compute Unified Device Architecture (CUDA) which is used to accelerate the execution of loops with many repetitions. Furthermore, we also use this technique to accelerate Monte Carlo simulations. In addition, we visualize fault tree so that the user is able to generate fault tree in detail using our developed software and can execute it. The computational outcomes validate the effectiveness of the suggested approach, as we approached about 310 times speed-up in large fault trees.
机译:关键系统的可靠性分析可以通过故障树分析来执行。用于故障树分析的方法之一是蒙特卡洛模拟。因此,本文的目的是展示一种可加速Monte Carlo仿真的算法,该算法可在GPU中使用并行计算来分析故障树。为此,我们使用故障时间树通过Compute Unified Device Architecture(CUDA)对故障树进行建模,该结构用于加速执行具有许多重复的循环。此外,我们还使用此技术来加速蒙特卡洛模拟。此外,我们将故障树可视化,以便用户能够使用我们开发的软件详细生成故障树并执行它。计算结果验证了所建议方法的有效性,因为我们在大型故障树中的速度提高了约310倍。

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