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Implementation of the Lattice Boltzmann Method on Heterogeneous Hardware and Platforms using OpenCL

机译:使用OpenCL在异构硬件和平台上实现Lattice Boltzmann方法

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The Lattice Boltzmann method (LBM) has become an alternative method for computational fluid dynamics with a wide range of applications. Besides its numerical stability and accuracy, one of the major advantages of LBM is its relatively easy parallelization and, hence, it is especially well fitted to many-core hardware as graphics processing units (GPU). The majority of work concerning LBM implementation on GPU's has used the CUDA programming model, supported exclusively by NVIDIA. Recently, the open standard for parallel programming of heterogeneous systems (OpenCL) has been introduced. OpenCL standard matures and is supported on processors from most vendors. In this paper, we make use of the OpenCL framework for the lattice Boltzmann method simulation, using hardware accelerators - AMD ATI Radeon GPU, AMD Dual-Core CPU and NVIDIA GeForce GPU's. Application has been developed using a combination of Java and OpenCL programming languages. Java bindings for OpenCL have been utilized. This approach offers the benefits of hardware and operating system independence, as well as speeding up of lattice Boltzmann algorithm. It has been showed that the developed lattice Boltzmann source code can be executed without modification on all of the used hardware accelerators. Performance results have been presented and compared for the hardware accelerators that have been utilized.
机译:格子玻尔兹曼方法(LBM)已成为具有广泛应用的流体动力学计算的替代方法。除了其数值稳定性和准确性外,LBM的主要优点之一是其相对容易的并行化,因此,它特别适合作为图形处理单元(GPU)应用于多核硬件。有关在GPU上实施LBM的大多数工作都使用了NVIDIA独家支持的CUDA编程模型。最近,引入了异构系统并行编程的开放标准(OpenCL)。 OpenCL标准已经成熟并且在大多数供应商的处理器上受支持。在本文中,我们使用OpenCL框架通过硬件加速器-AMD ATI Radeon GPU,AMD双核CPU和NVIDIA GeForce GPU进行了格子Boltzmann方法仿真。应用程序是使用Java和OpenCL编程语言的组合开发的。已使用OpenCL的Java绑定。这种方法提供了硬件和操作系统独立性以及加快晶格Boltzmann算法的优势。已经表明,可以在不对所有使用的硬件加速器进行修改的情况下执行所开发的格子Boltzmann源代码。对于已使用的硬件加速器,已经给出并比较了性能结果。

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