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Abstract: Matrix Decomposition Based Conjugate Gradient Solver for Poisson Equation

机译:摘要:基于矩阵分解的泊松方程共轭梯度解法

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摘要

Finding a fast solver for the Poisson equation is important for many scientific applications. In this work, we design and develop a matrix decomposition based Conjugate Gradient (CG) solver, which leverages Graphics Processing Unit (GPU) clusters to accelerate the calculation of the Poisson equation. Our experiments show that the new CG solver is highly scalable and achieves significant speedup over a CPU-based Multi-Grid (MG) solver.
机译:寻找泊松方程的快速求解器对于许多科学应用都很重要。在这项工作中,我们设计和开发了基于矩阵分解的共轭梯度(CG)求解器,该求解器利用图形处理单元(GPU)簇来加速泊松方程的计算。我们的实验表明,新的CG求解器具有高度的可扩展性,并且与基于CPU的多网格(MG)求解器相比,可以显着提高速度。

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