求解多核系统三维流固耦合问题的并行库

Prateek Nagar, Fengguang Song, Luoding Zhu, Lan Lin
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引用次数: 10

摘要

可变形结构在生物、医学、生命科学和海洋工程等领域有着广泛的应用。我们之前的工作创建了一种求解流固耦合问题的数值方法,称为LBM-IB方法[1]。我们的LBM-IB方法特别适用于模拟沉浸在移动粘性流体中的柔性(或弹性)结构。流固耦合问题以其对计算资源的大量需求而闻名。今天,解决许多现实世界的FSI问题仍然具有挑战性。为了更有效地解决大规模流固耦合问题,本文设计了一个基于多核心体系结构共享内存的并行LBM-IB库。我们从一个连续的版本开始,扩展到两个不同的并行版本。本文首先介绍了LBM-IB方法的数学背景,然后以序列版本为基础,给出了我们实现的计算核和算法。接下来,介绍两个并行程序:一个Open MP实现和一个使用pthread的基于多维数据集的并行实现。基于多维数据集的实现建立在我们新的以多维数据集为中心的算法之上,其中所有数据都存储在多维数据集中,并且以以数据为中心的方式在单个多维数据集上执行计算。通过利用更好的数据局部性和细粒度块并行性,基于立方体的并行实现能够在64核计算机系统上比Open MP实现高出53%。
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LBM-IB: A Parallel Library to Solve 3D Fluid-Structure Interaction Problems on Manycore Systems
Deformable structures are abundant in various domains such as biology, medicine, life sciences, and ocean engineering. Our previous work created a numerical method, named LBM-IB method [1], to solve the fluid-structure interaction (FSI) problems. Our LBM-IB method is particularly suitable for simulating flexible (or elastic) structures immersed in a moving viscous fluid. Fluid-structure interaction problems are well known for their heavy demands on computing resources. Today, it is still challenging to resolve many real-world FSI problems. In order to solve large-scale fluid-structure interactions more efficiently, in this paper, we design a parallel LBM-IB library on shared memory many core architectures. We start from a sequential version, which is extended to two different parallel versions. The paper first introduces the mathematical background of the LBM-IB method, then uses the sequential version as a ground to present our implemented computational kernels and the algorithm. Next, it describes the two parallel programs: an Open MP implementation and a cube-based parallel implementation using Pthreads. The cube-based implementation builds upon our new cube-centric algorithm where all the data are stored in cubes and computations are performed on individual cubes in a data-centric manner. By exploiting better data locality and fine-grain block parallelism, the cube-based parallel implementation is able to outperform the Open MP implementation by up to 53% on 64-core computer systems.
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