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Shared-Memory Parallelization of the Fast Marching Method Using an Overlapping Domain-Decomposition Approach

机译:使用重叠域分解方法的快速行进方法的共享内存并行化

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The fast marching method is used to compute a monotone front propagation of anisotropic nature by solving the eikonal equation. Due to the sequential nature of the original algorithm, parallel approaches presented so far were unconvincing. In this work, we introduce a shared-memory parallelization approach which is based on an overlapping domain decomposition technique. We introduce our parallel algorithm of the fast marching method tailored to shared-memory environments and discuss benchmark results based on a C++ implementation using OpenMP. We compare the sequential execution performance as well as the accuracy with reference implementations of the fast marching method and the fast iterative method; the latter is also used to evaluate the parallel scalability. Our shared-memory parallel fast marching method convinces both with regard to serial and parallel execution performance as well as with respect to accuracy.
机译:快速行进方法用于通过求解尖锐方程来计算各向异性性质的单调正面传播。由于原始算法的顺序性质,到目前为止呈现的并行方法是令人难以置信的。在这项工作中,我们介绍了一种基于重叠域分解技术的共享内存并行化方法。我们介绍了我们对共享内存环境量身定制的快速游行方法的并行算法,并根据使用OpenMP的基于C ++实现讨论基准结果。我们比较顺序执行性能以及快速行进方法的参考实现和快速迭代方法的准确性;后者也用于评估并行可扩展性。我们的共享内存并行快速行进方法在串行和并行执行性能以及准确性方面阐述。

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