We present a new, high-performance coupled electrodynamics-micromagnetics solver for full physical modeling of signals in microelectronic circuitry. The overall strategy couples a finite-difference time-domain (FDTD) approach for Maxwell's equations to a magnetization model described by the Landau-Lifshitz-Gilbert (LLG) equation. The algorithm is implemented in the Exascale Computing Project software framework, AMReX, which provides effective scalability on manycore and GPU-based supercomputing architectures. Furthermore, the code leverages ongoing developments of the Exascale Application Code, WarpX, primarily developed for plasma wakefield accelerator modeling. Our novel temporal coupling scheme provides second-order accuracy in space and time by combining the integration steps for the magnetic field and magnetization into an iterative sub-step that includes a trapezoidal discretization for the magnetization. The performance of the algorithm is demonstrated by the excellent scaling results on NERSC multicore and GPU systems, with a significant (59x) speedup on the GPU using a node-by-node comparison. We demonstrate the utility of our code by performing simulations of an electromagnetic waveguide and a magnetically tunable filter.
翻译:我们为微电子电路中信号的全面物理建模提出了一个新的高性能电动和微磁学解决方案。总体战略将Maxwell的等式的有限差异时间区(FDTD)法与Landau-Lifshitz-Gilbert(LLLG)等式描述的磁化模型结合起来。算法在Exacal 计算机项目软件框架AMREX中实施,它为许多核心和基于GPU的超计算结构提供了有效的缩放性。此外,该代码利用Exascal应用代码(WarpX)的不断开发,主要是为等离子体后场加速器加速模型的开发。我们新的时间组合计划将磁场和磁化的整合步骤合并成一个迭接子步骤,其中包括磁场的诱杀离离分解。该算法的性能表现表现在NERSC多极和GPU系统中的极佳的缩放效果中,在GPUPU上大大(59x)加速了(59x)主要为等离子场加速器加速模型模拟地电磁波变压。