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Early Experience on Porting and Running a Lattice Boltzmann Code on the Xeon-phi Co-Processor

机译:在Xeon-phi协处理器上移植和运行Lattice Boltzmann代码的早期经验

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In this paper we report on our early experience on porting, optimizing and benchmarking a Lattice Boltzmann (LB) code on the Xeon-Phi co-processor, the first generally available version of the newMany Integrated Core(MIC) architecture, developed by Intel. We consider as a test-bed a state-of-the-art LB model, that accurately reproduces the thermo-hydrodynamics of a 2D- fluid obeying the equations of state of a perfect gas. The regular structure of LB algorithms makes it relatively easy to identify a large degree of available parallelism. However, mapping a large fraction of this parallelism onto this new class of processors is not straightforward. The D2Q37 LB algorithm considered in this paper is an appropriate test-bed for this architecture since the critical computing kernels require high performances both in terms of memory bandwidth for sparse memory access patterns and number crunching capability. We describe our implementation of the code, that builds on previous experience made on other (simpler) many-core processors and GPUs, present benchmark results and measure performances, and finally compare with the results obtained by previous implementations developed on state-of-the-art classic multi-core CPUs and GP-GPUs.
机译:在本文中,我们报告了我们在Xeon-Phi协处理器上移植,优化和测试Lattice Boltzmann(LB)代码的早期经验,Xeon-Phi协处理器是Intel开发的newMany Integrated Core(MIC)架构的第一个通用版本。我们将最先进的LB模型视为试验台,该模型可以精确地再现2D流体的热流体动力学,并遵循理想气体的状态方程。 LB算法的规则结构使识别大量可用并行度相对容易。然而,将这种并行性的很大一部分映射到这种新型的处理器上并不容易。本文中考虑的D2Q37 LB算法是该体系结构的合适测试平台,因为关键的计算内核在稀疏内存访问模式的内存带宽和数字运算能力方面都需要高性能。我们描述代码的实现,该代码的实现基于在其他(或更简单)的多核处理器和GPU上的先前经验,提供基准测试结果并衡量性能,最后将其与基于最新状态开发的先前实现所获得的结果进行比较先进的经典多核CPU和GP-GPU。

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