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首页> 外文期刊>International Journal for Numerical Methods in Engineering >OpenCL-based implementation of an unstructured edge-based finite element convection-diffusion solver on graphics hardware
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OpenCL-based implementation of an unstructured edge-based finite element convection-diffusion solver on graphics hardware

机译:图形硬件上基于OpenCL的非结构化基于边缘的有限元对流扩散求解器的实现

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摘要

The solution of problems in computational fluid dynamics (CFD) represents a classical field for the application of advanced numerical methods. Many different approaches were developed over the years to address CFD applications. Good examples are finite volumes, finite differences (FD), and finite elements (FE) but also newer approaches such as the lattice-Boltzmann (LB), smooth particle hydrodynamics or the particle finite element method. FD and LB methods on regular grids are known to be superior in terms of raw computing speed, but using such regular discretization represents an important limitation in dealing with complex geometries. Here, we concentrate on unstructured approaches which are less common in the GPU world. We employ a nonstandard FE approach which leverages an optimized edge-based data structure allowing a highly parallel implementation. Such technique is applied to the 'convection-diffusion' problem, which is often considered as a first step towards CFD because of similarities to the nonconservative form of the Navier-Stokes equations. In this regard, an existing highly optimized parallel OpenMP solver is ported to graphics hardware based on the OpenCL platform. The optimizations performed are discussed in detail. A number of benchmarks prove that the GPU-accelerated OpenCL code consistently outperforms the OpenMP version.
机译:计算流体力学(CFD)中的问题解决方案代表了先进数值方法应用的经典领域。多年来,开发了许多不同的方法来解决CFD应用问题。很好的例子是有限体积,有限差分(FD)和有限元(FE),还有更新的方法,例如晶格玻尔兹曼(LB),光滑粒子流体动力学或粒子有限元方法。众所周知,常规网格上的FD和LB方法在原始计算速度方面是优越的,但是使用这种常规离散化是处理复杂几何图形的重要限制。在这里,我们专注于非结构化方法,这种方法在GPU领域并不常见。我们采用非标准的有限元方法,该方法利用优化的基于边缘的数据结构来实现高度并行的实现。这种技术应用于“对流扩散”问题,由于与Navier-Stokes方程的非保守形式相似,通常被认为是CFD的第一步。在这方面,现有的高度优化的并行OpenMP求解器已移植到基于OpenCL平台的图形硬件上。详细讨论了执行的优化。许多基准测试证明,GPU加速的OpenCL代码始终优于OpenMP版本。

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