\end{figure}\r
\r
\r
-Concerning the experiments some other remarks are interesting.\r
-\begin{itemize}\r
-\item We have tested other examples of PETSc/KSP (ex29, ex45, ex49). For all these\r
- examples, we have also obtained similar gains between GMRES and TSIRM but\r
- those examples are not scalable with many cores. In general, we had some\r
- problems with more than $4,096$ cores.\r
-\item We have tested many iterative solvers available in PETSc. In fact, it is\r
- possible to use most of them with TSIRM. From our point of view, the condition\r
- to use a solver inside TSIRM is that the solver must have a restart\r
- feature. More precisely, the solver must support to be stopped and restarted\r
- without decreasing its convergence. That is why with GMRES we stop it when it\r
- is naturally restarted (\emph{i.e.} with $m$ the restart parameter). The\r
- Conjugate Gradient (CG) and all its variants do not have ``restarted'' version\r
- in PETSc, so they are not efficient. They will converge with TSIRM but not\r
- quickly because if we compare a normal CG with a CG which is stopped and\r
- restarted every 16 iterations (for example), the normal CG will be far more\r
- efficient. Some restarted CG or CG variant versions exist and may be\r
- interesting to study in future works.\r
-\end{itemize}\r
%%%*********************************************************\r
%%%*********************************************************\r
\r
\r
\subsection{Nonlinear problems in parallel}\r
\r
-\begin{table*}[htbp]\r
-\begin{center}\r
-\begin{tabular}{|r|r|r|r|r|r|r|r|} \r
-\hline\r
-\r
- nb. cores & \multicolumn{2}{c|}{FGMRES/ASM} & \multicolumn{2}{c|}{TSIRM CGLS/ASM} & gain& \multicolumn{2}{c|}{FGMRES/HYPRE} \\ \r
-\cline{2-5} \cline{7-8}\r
- & Time & \# Iter. & Time & \# Iter. & & Time & \# Iter. \\\hline \hline\r
- 512 & 5.54 & 685 & 2.5 & 570 & 2.21 & 128.9 & 9 \\\r
- 2048 & 14.95 & 1,560 & 4.32 & 746 & 3.48 & 335.7 & 9 \\\r
- 4096 & 25.13 & 2,369 & 5.61 & 859 & 4.48 & >1000 & -- \\\r
- 8192 & 44.35 & 3,197 & 7.6 & 1083 & 5.84 & >1000 & -- \\\r
-\r
-\hline\r
-\r
-\end{tabular}\r
-\caption{Comparison of FGMRES and TSIRM for ex45 of PETSc/KSP with two preconditioner (ASM and HYPRE) having 25,000 components per core on Curie ($\epsilon_{tsirm}=1e-10$, $max\_iter_{kryl}=30$, $s=12$, $max\_iter_{ls}=15$, $\epsilon_{ls}=1e-40$), time is expressed in seconds.}\r
-\label{tab:06}\r
-\end{center}\r
-\end{table*}\r
\r
\r
\begin{figure}[htbp]\r
\end{table*}\r
\r
\r
-\subsection{Influcence of parameters for TSIRM}\r
+\subsection{Influence of parameters for TSIRM}\r
+\r
+\r
+\r
+\r
+\r
+\subsection{Experiments conclusions }\r
+\r
+{\bf A refaire}\r
+\r
+Concerning the experiments some other remarks are interesting.\r
+\begin{itemize}\r
+\item We have tested other examples of PETSc/KSP (ex29, ex45, ex49). For all these\r
+ examples, we have also obtained similar gains between GMRES and TSIRM but\r
+ those examples are not scalable with many cores. In general, we had some\r
+ problems with more than $4,096$ cores.\r
+\item We have tested many iterative solvers available in PETSc. In fact, it is\r
+ possible to use most of them with TSIRM. From our point of view, the condition\r
+ to use a solver inside TSIRM is that the solver must have a restart\r
+ feature. More precisely, the solver must support to be stopped and restarted\r
+ without decreasing its convergence. That is why with GMRES we stop it when it\r
+ is naturally restarted (\emph{i.e.} with $m$ the restart parameter). The\r
+ Conjugate Gradient (CG) and all its variants do not have ``restarted'' version\r
+ in PETSc, so they are not efficient. They will converge with TSIRM but not\r
+ quickly because if we compare a normal CG with a CG which is stopped and\r
+ restarted every 16 iterations (for example), the normal CG will be far more\r
+ efficient. Some restarted CG or CG variant versions exist and may be\r
+ interesting to study in future works.\r
+\end{itemize}\r
\r
%%ENDNEW\r
\r
+\r
%%%*********************************************************\r
%%%*********************************************************\r
\section{Conclusion}\r
