Abstract: A high-performance parallel LU direct solver based on the Kokkos framework is developed for solving large complex dense linear systems arising from the method of moments(MoM)in electromagnetic simulations on accelerator-based heterogeneous systems.The impedance matrix and excitation vector are efficiently filled in parallel on the GPU using Kokkos∷parallel_for.Based on the computed solution,the radar cross section(RCS)is obtained on the host by traversing observation angles and synthesizing the scattered field.The overall workflow is efficient and demonstrates good scalability.Performance evaluation is conducted on the “ORISE” supercomputing platform equipped with deep computing unit(DCU)accelerators.The impact of two-dimensional processor grid strategies on performance and communication overhead is analyzed.Under 16 processes,increasing the number of processors per row from 1 to 4 results in a 40.7% performance improvement and a reduction in communication overhead from 64.71% to 55.07%.Proper processor grid configuration effectively balances computation and communication,significantly reducing communication overhead and enhancing overall parallel efficiency.With 64 DCUs,the solver achieves a peak performance of 16 655.73 GFLOP/s,and when scaled to 2 048 DCUs,the performance increases to 58 338.90 GFLOP/s,showing good scalability.In the weak scalability test,the solver attains a parallel efficiency of 24.45% when scaling from 4 to 2 048 DCUs.These results indicate that the Kokkos-based direct solver delivers strong performance and is well-suited for large-scale electromagnetic simulation on heterogeneous high-performance computing platforms.

Key words: Kokkos, Method of moments, Parallel LU decomposition, Deep computing unit, Heterogeneous computing