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| author |  Gael Guennebaud <g.gael@free.fr> | 2015-06-26 10:49:40 +0200 |
|---|---|---|
| committer | Gael Guennebaud <g.gael@free.fr> | 2015-06-26 10:49:40 +0200 |
| commit | 555b9c684346129057b14d73db64a75274fdfe0f (patch) | |
| tree | d35749e34b390790a9cd12c7e9309391baf69309 /doc | |
| parent | 53b930887d118af5204840231f08b3307addce4e (diff) | |
Doc: explain perf and multithreading issues in sparse iterative solvers
Diffstat (limited to 'doc')
| -rw-r--r-- | doc/SparseLinearSystems.dox | 2 | ||||
| -rw-r--r-- | doc/TopicMultithreading.dox | 8 |
2 files changed, 7 insertions, 3 deletions
diff --git a/doc/SparseLinearSystems.dox b/doc/SparseLinearSystems.dox index 13741280a..48c18f46f 100644 --- a/doc/SparseLinearSystems.dox +++ b/doc/SparseLinearSystems.dox @@ -21,7 +21,7 @@ They are summarized in the following table: <tr><td>ConjugateGradient</td><td>\link IterativeLinearSolvers_Module IterativeLinearSolvers \endlink</td><td>Classic iterative CG</td><td>SPD</td><td>Preconditionning</td> <td>built-in, MPL2</td> <td>Recommended for large symmetric problems (e.g., 3D Poisson eq.)</td></tr> -<tr><td>LSCG</td><td>\link IterativeLinearSolvers_Module IterativeLinearSolvers \endlink</td><td>CG for rectangular least-square problem</td><td>Rectangular</td><td>Preconditionning</td> +<tr><td>LeastSquaresConjugateGradient</td><td>\link IterativeLinearSolvers_Module IterativeLinearSolvers \endlink</td><td>CG for rectangular least-square problem</td><td>Rectangular</td><td>Preconditionning</td> <td>built-in, MPL2</td> <td>Solve for min |A'Ax-b|^2 without forming A'A</td></tr> <tr><td>BiCGSTAB</td><td>\link IterativeLinearSolvers_Module IterativeLinearSolvers \endlink</td><td>Iterative stabilized bi-conjugate gradient</td><td>Square</td><td>Preconditionning</td> diff --git a/doc/TopicMultithreading.dox b/doc/TopicMultithreading.dox index e22e1c613..66028d7a8 100644 --- a/doc/TopicMultithreading.dox +++ b/doc/TopicMultithreading.dox @@ -22,8 +22,12 @@ n = Eigen::nbThreads( ); You can disable Eigen's multi threading at compile time by defining the EIGEN_DONT_PARALLELIZE preprocessor token. Currently, the following algorithms can make use of multi-threading: - * general matrix - matrix products - * PartialPivLU + - general dense matrix - matrix products + - PartialPivLU + - row-major-sparse * dense vector/matrix products + - ConjugateGradient with \c Lower|Upper as the \c UpLo template parameter. + - BiCGSTAB with a row-major sparse matrix format. + - LeastSquaresConjugateGradient \section TopicMultiThreading_UsingEigenWithMT Using Eigen in a multi-threaded application |