X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/GMRES2stage.git/blobdiff_plain/448491bcbd3b99bf6aaeed32bae4854925405051..b86c85516c6889f5d743154ed489941a59ae307b:/IJHPCN/paper.tex

diff --git a/IJHPCN/paper.tex b/IJHPCN/paper.tex
index 21fa922..4c711cc 100644
--- a/IJHPCN/paper.tex
+++ b/IJHPCN/paper.tex
@@ -776,25 +776,6 @@ taken into account with TSIRM.
 \end{figure}
 
 
-Concerning the  experiments some  other remarks are  interesting.
-\begin{itemize}
-\item We have tested other examples  of PETSc/KSP (ex29, ex45, ex49).  For all these
-  examples,  we have also  obtained similar  gains between  GMRES and  TSIRM but
-  those  examples are  not scalable  with many  cores. In  general, we  had some
-  problems with more than $4,096$ cores.
-\item We have tested many iterative  solvers available in PETSc.  In fact, it is
-  possible to use most of them with TSIRM. From our point of view, the condition
-  to  use  a  solver inside  TSIRM  is  that  the  solver  must have  a  restart
-  feature. More precisely,  the solver must support to  be stopped and restarted
-  without decreasing its convergence. That is  why with GMRES we stop it when it
-  is  naturally restarted (\emph{i.e.}   with $m$  the restart  parameter).  The
-  Conjugate Gradient (CG) and all its variants do not have ``restarted'' version
-  in PETSc,  so they are not efficient.   They will converge with  TSIRM but not
-  quickly because  if we  compare a  normal CG with  a CG  which is  stopped and
-  restarted every  16 iterations (for example),  the normal CG will  be far more
-  efficient.   Some  restarted  CG or  CG  variant  versions  exist and  may  be
-  interesting to study in future works.
-\end{itemize}
 %%%*********************************************************
 %%%*********************************************************
 
@@ -803,26 +784,6 @@ Concerning the  experiments some  other remarks are  interesting.
 
 \subsection{Nonlinear problems in parallel}
 
-\begin{table*}[htbp]
-\begin{center}
-\begin{tabular}{|r|r|r|r|r|r|r|r|} 
-\hline
-
-  nb. cores   & \multicolumn{2}{c|}{FGMRES/ASM} & \multicolumn{2}{c|}{TSIRM CGLS/ASM} & gain& \multicolumn{2}{c|}{FGMRES/HYPRE}   \\ 
-\cline{2-5} \cline{7-8}
-                    & Time  & \# Iter.  & Time  & \# Iter. &        & Time  & \# Iter.   \\\hline \hline
-   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 &  --   \\
-
-\hline
-
-\end{tabular}
-\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.}
-\label{tab:06}
-\end{center}
-\end{table*}
 
 
 \begin{figure}[htbp]
@@ -877,10 +838,39 @@ Concerning the  experiments some  other remarks are  interesting.
 \end{table*}
 
 
-\subsection{Influcence of parameters for TSIRM}
+\subsection{Influence of parameters for TSIRM}
+
+
+
+
+
+\subsection{Experiments conclusions }
+
+{\bf A refaire}
+
+Concerning the  experiments some  other remarks are  interesting.
+\begin{itemize}
+\item We have tested other examples  of PETSc/KSP (ex29, ex45, ex49).  For all these
+  examples,  we have also  obtained similar  gains between  GMRES and  TSIRM but
+  those  examples are  not scalable  with many  cores. In  general, we  had some
+  problems with more than $4,096$ cores.
+\item We have tested many iterative  solvers available in PETSc.  In fact, it is
+  possible to use most of them with TSIRM. From our point of view, the condition
+  to  use  a  solver inside  TSIRM  is  that  the  solver  must have  a  restart
+  feature. More precisely,  the solver must support to  be stopped and restarted
+  without decreasing its convergence. That is  why with GMRES we stop it when it
+  is  naturally restarted (\emph{i.e.}   with $m$  the restart  parameter).  The
+  Conjugate Gradient (CG) and all its variants do not have ``restarted'' version
+  in PETSc,  so they are not efficient.   They will converge with  TSIRM but not
+  quickly because  if we  compare a  normal CG with  a CG  which is  stopped and
+  restarted every  16 iterations (for example),  the normal CG will  be far more
+  efficient.   Some  restarted  CG or  CG  variant  versions  exist and  may  be
+  interesting to study in future works.
+\end{itemize}
 
 %%ENDNEW
 
+
 %%%*********************************************************
 %%%*********************************************************
 \section{Conclusion}
