Conjugate Gradient and Lanczos Methods for Sparse Matrices on Distributed Memory Multiprocessors

@article{Basermann1997ConjugateGA,
  title={Conjugate Gradient and Lanczos Methods for Sparse Matrices on Distributed Memory Multiprocessors},
  author={Achim Basermann},
  journal={J. Parallel Distributed Comput.},
  year={1997},
  volume={45},
  pages={46-52}
}
  • A. Basermann
  • Published 25 August 1997
  • Computer Science
  • J. Parallel Distributed Comput.
Conjugate gradient methods for solving sparse systems of linear equations and Lanczos algorithms for sparse symmetric eigenvalue problems play an important role in numerical methods for solving discretized partial differential equations. When these iterative solvers are parallelized on a multiprocessor system with distributed memory, the data distribution and the communication scheme?depending on the data structures used for the sparse coefficient matrices?are crucial for efficient execution… 

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