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<p>This study tackles the computational bottleneck of matrix exponential calculations in Exponential Time Differencing (ETD) methods through a novel parallel algorithm that synergizes MPI and OpenMP technologies. By partitioning the matrix among MPI processes and leveraging OpenMP for localized matrix multiplication, our approach significantly enhances the ability to address diffuse-interface problems at previously unattainable mesh sizes for serial computation for general boundary conditions. Through comprehensive performance evaluations, we demonstrate the algorithm’s substantial improvements in efficiency and speed, showcasing a major leap forward in the computational capabilities of ETD methods for complex applications.</p>

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Parallelization of the Exponential Time Differencing Method for Solving Diffuse-Interface Models

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年7月15日

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  • Meng-Huo Chen,
  • Yuanqing Wu,
  • Xiaoyu Feng,
  • Shuyu Sun

摘要

This study tackles the computational bottleneck of matrix exponential calculations in Exponential Time Differencing (ETD) methods through a novel parallel algorithm that synergizes MPI and OpenMP technologies. By partitioning the matrix among MPI processes and leveraging OpenMP for localized matrix multiplication, our approach significantly enhances the ability to address diffuse-interface problems at previously unattainable mesh sizes for serial computation for general boundary conditions. Through comprehensive performance evaluations, we demonstrate the algorithm’s substantial improvements in efficiency and speed, showcasing a major leap forward in the computational capabilities of ETD methods for complex applications.