Search results for: SPMV

• 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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• Jacobi and gauss-seidel preconditioned complex conjugate gradient method with GPU acceleration for finite element method

  Publication

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

  - Year 2010

  In this paper two implementations of iterative solvers for solving complex symmetric and sparse systems resulting from finite element method applied to wave equation are discussed. The problem under investigation is a dielectric resonator antenna (DRA) discretized by FEM with vector elements of the second order (LT/QN). The solvers use the preconditioned conjugate gradient (pcg) method implemented on Graphics Processing Unit (GPU)...

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