A fine-grained parallelization of the immersed boundary method

IF 3.5 3区 计算机科学 Q2 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE
A. Kassen, Varun Shankar, A. Fogelson
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引用次数: 0

Abstract

We present new algorithms for the parallelization of Eulerian–Lagrangian interaction operations in the immersed boundary method. Our algorithms rely on two well-studied parallel primitives: key-value sort and segmented reduce. The use of these parallel primitives allows us to implement our algorithms on both graphics processing units (GPUs) and on other shared-memory architectures. We present strong and weak scaling tests on problems involving scattered points and elastic structures. Our tests show that our algorithms exhibit near-ideal scaling on both multicore CPUs and GPUs.
一种细粒度的浸入边界并行化方法
提出了浸入边界法中欧拉-拉格朗日相互作用运算并行化的新算法。我们的算法依赖于两个研究得很好的并行原语:键值排序和分段约简。使用这些并行原语允许我们在图形处理单元(gpu)和其他共享内存架构上实现我们的算法。给出了涉及散点和弹性结构问题的强、弱尺度检验。我们的测试表明,我们的算法在多核cpu和gpu上都表现出接近理想的可伸缩性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
International Journal of High Performance Computing Applications
International Journal of High Performance Computing Applications 工程技术-计算机:跨学科应用
CiteScore
6.10
自引率
6.50%
发文量
32
审稿时长
>12 weeks
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