Search results for: SLICED ELLR-T

• A memory efficient and fast sparse matrix vector product on a Gpu

  Publication

  • A. Dziekoński
  • A. Lamęcki
  • M. Mrozowski

  - Progress in Electromagnetics Research-PIER - Year 2011

  This paper proposes a new sparse matrix storage format which allows an efficient implementation of a sparse matrix vector product on a Fermi Graphics Processing Unit (GPU). Unlike previous formats it has both low memory footprint and good throughput. The new format, which we call Sliced ELLR-T has been designed specifically for accelerating the iterative solution of a large sparse and complex-valued system of linear equations arising...

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• A GPU Solver for Sparse Generalized Eigenvalue Problems with Symmetric Complex-Valued Matrices Obtained Using Higher-Order FEM

  Publication

  • A. Dziekoński
  • M. Mrozowski

  - IEEE Access - Year 2018

  The paper discusses a fast implementation of the stabilized locally optimal block preconditioned conjugate gradient (sLOBPCG) method, using a hierarchical multilevel preconditioner to solve nonHermitian sparse generalized eigenvalue problems with large symmetric complex-valued matrices obtained using the higher-order finite-element method (FEM), applied to the analysis of a microwave resonator. The resonant frequencies of the low-order...

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