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Performance Optimization of D3Q19 Lattice Boltzmann Kernels on Intel KNL

机译:Intel Knl上D3Q19格子Boltzmann内核的性能优化

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This work discusses and assesses the impact of fundamental code optimization steps performed to maximize computing performances and memory throughput on Intel? Knights Landing (KNL) processor for Lattice Boltzmann (LB) applications. The benefits of using different memory data layouts is presented in regards to the most computationally intensive kernels of such applications, reporting performance results measured for the LBE3D code developed at the Applied Physics Department of the Eindhoven University of Technology, and run on a single KNL node for a common flow simulation case. We finally analyze and discuss the impact of different memory layouts on energy efficiency.
机译:这项工作讨论并评估了基本代码优化步骤的影响,以最大限度地提高英特尔的计算性能和内存吞吐量?骑士降落(KNL)处理器用于格子Boltzmann(LB)应用。在此应用的最具计算密集的内核中,提供了使用不同内存数据布局的好处,报告了在埃因霍温技术大学应用物理部门开发的LBE3D代码测量的绩效结果,并在单个KNL节点上运行对于共同的流动模拟案例。我们终于分析并讨论了不同记忆布局对能效的影响。

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