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Accelerated Monte Carlo Simulation on the Chemical Stage in Water Radiolysis using GPU

机译:使用GPU在水分解中化学阶段的加速Monte Carlo模拟

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摘要

The accurate simulation of water radiolysis is an important step to understand the mechanisms of radiobiology and quantitatively test some hypotheses regarding radiobiological effects. However, the simulation of water radiolysis is highly time consuming, taking hours or even days to be completed by a conventional CPU processor. This time limitation hinders cell-level simulations for a number of research studies. We recently initiated efforts to develop gMicroMC, a GPU-based fast microscopic MC simulation package for water radiolysis. The first step of this project focused on accelerating the simulation of the chemical stage, the most time consuming stage in the entire water radiolysis process. A GPU-friendly parallelization strategy was designed to address the highly correlated many-body simulation problem caused by the mutual competitive chemical reactions between the radiolytic molecules. Two cases were tested, using a 750 keV electron and a 5 MeV proton incident in pure water, respectively. The time-dependent yields of all the radiolytic species during the chemical stage were used to evaluate the accuracy of the simulation. The relative differences between our simulation and the Geant4-DNA simulation were on average 5.3% and 4.4% for the two cases. Our package, executed on an Nvidia Titan black GPU card, successfully completed the chemical stage simulation of the two cases within 599.2 s and 489.0 s. As compared with Geant4-DNA that was executed on an Intel i7-5500U CPU processor and needed 28.6 h and 26.8 h for the two cases using a single CPU core, our package achieved a speed-up factor of 171.1-197.2.
机译:准确地模拟水的放射分解是了解放射生物学机制并定量检验有关放射生物学影响的某些假设的重要步骤。但是,水辐射分解的模拟非常耗时,传统的CPU处理器需要花费数小时甚至数天才能完成。此时间限制阻碍了许多研究的细胞水平模拟。我们最近着手开发gMicroMC,这是一种基于GPU的用于水辐射分解的快速显微MC模拟程序包。该项目的第一步着重于加速化学阶段的仿真,化学阶段是整个水辐射分解过程中最耗时的阶段。设计了一种GPU友好的并行化策略,以解决由辐射分解分子之间相互竞争的化学反应引起的高度相关的多体模拟问题。测试了两种情况,分别使用入射在纯水中的750 keV电子和5 MeV质子。在化学阶段,所有辐射分解物种的时间依赖性产量均用于评估模拟的准确性。在这两种情况下,我们的模拟与Geant4-DNA模拟之间的相对差异平均分别为5.3%和4.4%。我们的软件包在Nvidia Titan黑色GPU卡上执行,在599.2 s和489.0 s内成功完成了这两种情况的化学阶段模拟。与在Intel i7-5500U CPU处理器上执行的Geant4-DNA相比,在两种情况下使用单个CPU内核分别需要28.6小时和26.8小时,我们的软件包实现了171.1-197.2的加速因子。

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  • 期刊名称 other
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  • 年(卷),期 -1(62),8
  • 年度 -1
  • 页码 3081–3096
  • 总页数 24
  • 原文格式 PDF
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