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arXiv physics/9611025physics.plasm-phphysics.comp-ph
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托卡马克湍流输运的大规模并行计算

Massively Parallel Computing of Turbulent Transport in Tokamaks

Jeremy Kepner, Scott Parker, Viktor Decyk

摘要:

随着回旋动力学模型的出现、低噪声非线性$δf$方法的发展以及计算能力的巨大提高,大尺度回旋动力学模拟已成为提高对托卡马克中异常输运的理解的重要工具。模拟非线性行为需要求解五维分布函数的扰动。我们使用一个粒子在细胞的方法来解决方程通过非线性特征方法。该代码已被并行化的各种architecures(C90,CM-5,T3 D)使用1-D区域分解沿环形轴,每个单元格中的粒子数保持近似恒定。粒子的准均匀分布,最大限度地减少了负载不平衡,加上粒子跨单元的相对较小的移动,最大限度地减少了通信,使这个问题非常适合大规模并行架构。我们提出的程序的性能作为处理器的数量和问题大小的函数,这表明了近乎完美的可扩展性的代码。此外,我们还讨论了从代码中获得的科学结果,以及随着下一代超级计算机的出现,将可解决的问题类型。

英文摘要:

With the advent of the gyrokinetic formalism, recent developments in low-noise nonlinear $δf$ methods, and enormous gains in computing power, large-scale gyrokinetic simulations have become an important tool for improved understanding of anomalous transport in tokamaks. Simulating the non-linear behaviour requires solving for the perturbations of distrbution function in five dimensions. We use a particle-in-cell approach to solve the equations via the non-linear characteristic method. The code has been parallelized for a variety of architecures (C90, CM-5, T3D) using a 1-D domain decomposition along the torroidal axis, for which the number of particles in each cell remains approximately constant. The quasi uniform distribution of particles, which minimizes load imbalance, coupled with the relatively small movement of particles across cells, which minimizes communications, makes this problem ideally suited to massively parallel architectures. We present the performance of the program as a function of number of processors and problem size, which demonstrates the near perfect scalability of the code. In addition, we discuss the scientific results obtained from the code and the types of problems that will be addressable as the next generation of super-computers become available.

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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