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Solving sparse systems: Difference between revisions

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There are many methods available for solving sparse systems. We compare some of them here.
There are many methods available for solving sparse systems. We compare some of them here.
Mathematica has the following methods available (https://reference.wolfram.com/language/ref/LinearSolve.html#DetailsAndOptions)
* direct: banded, cholesky, multifrontal (direct sparse LU)
* iterative: Krylov
Matlab has the following methods:
* direct: https://www.mathworks.com/help/matlab/ref/mldivide.html#bt42omx_head
* iterative: https://www.mathworks.com/help/matlab/math/systems-of-linear-equations.html#brzoiix, including bicgstab, gmres
Eigen has the following methods: (https://eigen.tuxfamily.org/dox-devel/group__TopicSparseSystems.html)
* direct: sparse LU
* iterative: bicgstab, cg
Solving a simple sparse system $A x = b$ with $A = \begin{bmatrix} \ddots & \ddots & \ddots && \\ & 1 & 1 & 1 & \\ && \ddots & \ddots & \ddots$ and $b = \begin{bmatrix} 1 \\ \vdots \\ 1 \end{bmatrix}$ with dimension $n$
has the following timings:

Revision as of 12:50, 15 March 2017

There are many methods available for solving sparse systems. We compare some of them here.

Mathematica has the following methods available (https://reference.wolfram.com/language/ref/LinearSolve.html#DetailsAndOptions)

  • direct: banded, cholesky, multifrontal (direct sparse LU)
  • iterative: Krylov

Matlab has the following methods:

Eigen has the following methods: (https://eigen.tuxfamily.org/dox-devel/group__TopicSparseSystems.html)

  • direct: sparse LU
  • iterative: bicgstab, cg

Solving a simple sparse system $A x = b$ with $A = \begin{bmatrix} \ddots & \ddots & \ddots && \\ & 1 & 1 & 1 & \\ && \ddots & \ddots & \ddots$ and $b = \begin{bmatrix} 1 \\ \vdots \\ 1 \end{bmatrix}$ with dimension $n$ has the following timings: