首页> 外文期刊>Journal of the American Society for Mass Spectrometry >Application of parallel hybrid algorithm in massively parallel GPGPU-the improved effective and efficient method for calculating coulombic interactions in simulations of many ions with SIMION
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Application of parallel hybrid algorithm in massively parallel GPGPU-the improved effective and efficient method for calculating coulombic interactions in simulations of many ions with SIMION

机译:并行混合算法在大规模并行GPGPU中的应用-一种改进的有效方法,可在SIMION模拟中计算库仑相互作用

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In our previous study, we introduced a new hybrid approach to effectively approximate the total force on each ion during a trajectory calculation in mass spectrometry device simulations, and the algorithm worked successfully with SIMION. We took one step further and applied the method in massively parallel general-purpose computing with GPU (GPGPU) to test its performance in simulations with thousands to over a million ions. We took extra care to minimize the barrier synchronization and data transfer between the host (CPU) and the device (GPU) memory, and took full advantage of the latency hiding. Parallel codes were written in CUDA C++ and implemented to SIMION via the user-defined Lua program. In this study, we tested the parallel hybrid algorithm with a couple of basic models and analyzed the performance by comparing it to that of the original, fully-explicit method written in serial code. The Coulomb explosion simulation with 128,000 ions was completed in 309 s, over 700 times faster than the 63 h taken by the original explicit method in which we evaluated two-body Coulomb interactions explicitly on one ion with each of all the other ions. The simulation of 1,024,000 ions was completed in 2650 s. In another example, we applied the hybrid method on a simulation of ions in a simple quadrupole ion storage model with 100,000 ions, and it only took less than 10 d. Based on our estimate, the same simulation is expected to take 5-7 y by the explicit method in serial code.
机译:在先前的研究中,我们引入了一种新的混合方法,可以在质谱设备模拟中的轨迹计算过程中有效地估算每个离子上的总力,并且该算法与SIMION一起成功运行。我们又迈出了一步,将该方法应用于带有GPU的大规模并行通用计算(GPGPU)中,以测试其在数千至上百万个离子中的性能。我们特别注意最小化主机(CPU)和设备(GPU)内存之间的屏障同步和数据传输,并充分利用了延迟隐藏功能。并行代码使用CUDA C ++编写,并通过用户定义的Lua程序实现给SIMION。在这项研究中,我们用几个基本模型测试了并行混合算法,并通过将其与用串行代码编写的原始的,完全显式的方法进行比较,分析了性能。在309 s内完成了使用128,000个离子的库仑爆炸模拟,比最初的显式方法所用的63 h快了700倍,在原始方法中,我们明确地评估了一个离子与所有其他离子的两体库仑相互作用。在2650 s内完成了1,024,000个离子的模拟。在另一个示例中,我们将混合方法应用于具有100,000个离子的简单四极离子存储模型中的离子模拟,并且只用了不到10 d的时间。根据我们的估计,通过串行代码中的显式方法,相同的仿真预计将花费5-7 y。

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