X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/GMRES2stage.git/blobdiff_plain/26119b98c896e296f4ec91c15272a9575fe250a9..7122f8d886bcd6191b7eee5017e8c96944ab7e56:/IJHPCN/paper.tex diff --git a/IJHPCN/paper.tex b/IJHPCN/paper.tex index 410b7ad..db5f791 100644 --- a/IJHPCN/paper.tex +++ b/IJHPCN/paper.tex @@ -911,8 +911,20 @@ taken into account with TSIRM. %%NEW +It is well-known that preconditioners have a very strong influence on the +convergence of linear systems. Previously, we have used some classical +preconditioners provided by PETSc. HYPRE~\cite{Falgout06} is a very efficient +preconditioner based on structured multigrid and element-based algebraic +multigrid algorithms. In Table~\ref{tab:06} we report an experiment that show it +reduces drastivally the number of iterations but sometimes it is very +time-consuming compared to other simpler precondititioners. In this table, we +can see that for $512$ and $2,048$ cores, HYPRE reduces drastically the number +of iterations for FGMRES to reach the convergence. However, it is very +time-consuming compared to TSIRM and FGMRES with the ASM preconditioner. For +$4,096$ and $8,192$ cores, FGMRES with HYPRE did not converge in less than 1000s +where FGMRES and TSIRM with the ASM converge very quickly. Finally, it can be +noticed that TSIRM is also faster than FGMRES and it requires less iterations. -{\bf example ex45/ksp à décrire et commenter en montrant que hypre est pourri avec cet exemple} \begin{table*}[htbp] \begin{center} @@ -925,7 +937,7 @@ taken into account with TSIRM. 512 & 5.54 & 685 & 2.5 & 570 & 2.21 & 128.9 & 9 \\ 2048 & 14.95 & 1,560 & 4.32 & 746 & 3.48 & 335.7 & 9 \\ 4096 & 25.13 & 2,369 & 5.61 & 859 & 4.48 & >1000 & -- \\ - 8192 & 44.35 & 3,197 & 7.6 & 1083 & 5.84 & >1000 & -- \\ + 8192 & 44.35 & 3,197 & 7.6 & 1,083 & 5.84 & >1000 & -- \\ \hline @@ -982,7 +994,7 @@ caption of the table. \end{center} \end{table*} -In Table~\cite{tab:08}, the results of the experiments with the example ex20 are +In Table~\ref{tab:08}, the results of the experiments with the example ex20 are reported. The block Jacobi preconditioner has also been used and CGLS to solve the minimization step for TSIRM. For this example, we can observ that the number of iterations for FMGRES increase drastically when the number of cores