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Efficient Parallel Preconditioned Conjugate Gradient Solver on GPU for FE Modeling of Electromagnetic Fields in Highly Dissipative Media

机译:GPU上的高效并行预处理共轭梯度求解器,用于高耗散介质中电磁场的有限元建模

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We present a performance analysis of a parallel implementation of preconditioned conjugate gradient solvers using graphic processing units with compute unified device architecture programming model. The solvers were optimized for the solution of sparse systems of equations arising from finite-element analysis of electromagnetic phenomena involved in the diffusion of underground currents in both steady state and under time-harmonic current excitation. We used both shifted incomplete Cholesky factorization and incomplete LU factorization as preconditioners. The results show a significant speedup using the graphics processing unit compared with a serial CPU implementation.
机译:我们介绍了使用图形处理单元和计算统一设备体系结构编程模型对并行预处理条件共轭梯度求解器的性能分析。对求解器进行了优化,以解决因电磁现象的有限元分析而产生的方程组稀疏问题,电磁现象涉及稳态和时谐波电流激励下地下电流的扩散。我们将移位的不完全Cholesky分解和不完全LU分解都用作前置条件。结果表明,与串行CPU实施相比,使用图形处理单元可以显着提高速度。

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