HemeLB格子Boltzmann仿真环境的性能分析与建模
Analyzing and Modeling the Performance of the HemeLB Lattice-Boltzmann Simulation Environment
摘要：
我们调查的性能HemeLB格子玻尔兹曼模拟器脑血管血流，旨在提供及时和临床相关的援助，神经外科医生。HemeLB针对稀疏几何形状进行了优化，支持交互式使用，并可扩展到32，768个核心，用于解决约8100万个网格位置的问题。我们获得了每秒295亿次站点更新的最大性能，对于高度稀疏的问题（5%的流体部分）只有11%的减速。我们提出了转向和可视化性能测量，并提供了一个模型，允许用户预测性能，从而确定如何在时间限制内以最大的精度运行模拟。
英文摘要：
We investigate the performance of the HemeLB lattice-Boltzmann simulator for cerebrovascular blood flow, aimed at providing timely and clinically relevant assistance to neurosurgeons. HemeLB is optimised for sparse geometries, supports interactive use, and scales well to 32,768 cores for problems with ~81 million lattice sites. We obtain a maximum performance of 29.5 billion site updates per second, with only an 11% slowdown for highly sparse problems (5% fluid fraction). We present steering and visualisation performance measurements and provide a model which allows users to predict the performance, thereby determining how to run simulations with maximum accuracy within time constraints.
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。
