ParILUT -用于gpu的并行门限ILU

H. Anzt, T. Ribizel, Goran Flegar, Edmond Chow, J. Dongarra
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引用次数: 14

摘要

在本文中,我们提出了在GPU架构上计算阈值ILU分解的第一种算法。提出的ParILUT-GPU算法基于交错并行不动点迭代,该迭代近似现有非零模式的不完全因子,并采用动态调整非零模式以适应问题特征的策略。这需要有效地选择阈值,将要丢弃的值从不完整的因素中分离出来,我们设计了一种针对gpu的新颖选择算法。ParILUT-GPU算法的所有组件都充分利用了最新一代NVIDIA GPU的功能,并且优于现有的多线程CPU实现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
ParILUT - A Parallel Threshold ILU for GPUs
In this paper, we present the first algorithm for computing threshold ILU factorizations on GPU architectures. The proposed ParILUT-GPU algorithm is based on interleaving parallel fixed-point iterations that approximate the incomplete factors for an existing nonzero pattern with a strategy that dynamically adapts the nonzero pattern to the problem characteristics. This requires the efficient selection of thresholds that separate the values to be dropped from the incomplete factors, and we design a novel selection algorithm tailored towards GPUs. All components of the ParILUT-GPU algorithm make heavy use of the features available in the latest NVIDIA GPU generations, and outperform existing multithreaded CPU implementations.
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