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Electromagnetic Simulations with 3D FEM and Intel Optane Persistent Memory
PublikacjaAbstract—Intel Optane persistent memory has the potential to induce a change in how high-performance calculations requiring a large system memory capacity are conducted. This article presents what this change may look like in the case of factorization of large sparse matrices describing electromagnetic problems arising in the 3D FEM analysis of passive highfrequency components. In numerical tests, the Intel oneAPI MKL PARDISO was...
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GPU-Accelerated LOBPCG Method with Inexact Null-Space Filtering for Solving Generalized Eigenvalue Problems in Computational Electromagnetics Analysis with Higher-Order FEM
PublikacjaThis paper presents a GPU-accelerated implementation of the Locally Optimal Block Preconditioned Conjugate Gradient (LOBPCG) method with an inexact nullspace filtering approach to find eigenvalues in electromagnetics analysis with higherorder FEM. The performance of the proposed approach is verified using the Kepler (Tesla K40c) graphics accelerator, and is compared to the performance of the implementation based on functions from...
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A Task-Scheduling Approach for Efficient Sparse Symmetric Matrix-Vector Multiplication on a GPU
PublikacjaIn this paper, a task-scheduling approach to efficiently calculating sparse symmetric matrix-vector products and designed to run on Graphics Processing Units (GPUs) is presented. The main premise is that, for many sparse symmetric matrices occurring in common applications, it is possible to obtain significant reductions in memory usage and improvements in performance when the matrix is prepared in certain ways prior to computation....