From: lilia <lilia@amazigh.bordeaux.inria.fr>
Date: Fri, 31 Jan 2014 16:50:48 +0000 (+0100)
Subject: 31-01-2014
X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/GMRES_For_Journal.git/commitdiff_plain/c23c850e5b39791f74aa368f865c42b57f2bc3d3?hp=8635cad758822d1aadb162d6318d6c4228a6314a

31-01-2014
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diff --git a/GMRES_Journal.tex b/GMRES_Journal.tex
index a4a026a..be3eccf 100644
--- a/GMRES_Journal.tex
+++ b/GMRES_Journal.tex
@@ -843,10 +843,44 @@ torso3                  & 183 863 292      & 25 682 514       & 613 250
 \end{center}
 \end{table}
 
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 %%% MODIF %%%
 \textcolor{red}{\bf In order to show the influence of the communications on a GPU cluster
 In tables, we compute the ratios of the computation time over the communication time to show the influence of the communications on a GPU cluster compared to a CPU cluster}
 
+\begin{table}%[!h]
+\begin{center}
+\begin{tabular}{|c|c|c|c|} 
+\hline
+Matrix            & Computation time & Communication time & Ratio \\ \hline \hline
+2cubes\_sphere    & 37.067 s         & 1434.512 s         & 0.026 \\
+ecology2          & 4.116 s          & 501.327 s          & 0.008 \\
+finan512          & 7.170 s          & 386.742 s          & 0.019 \\
+G3\_circuit       & 4.797 s          & 537.343 s          & 0.009 \\
+shallow\_water2   & 3.620 s          & 411.208 s          & 0.009 \\ 
+thermal2          & 6.902 s          & 511.618 s          & 0.013 \\ \hline \hline
+cage13            & 12.837 s         & 625.175 s          & 0.021 \\
+crashbasis        & 48.532 s         & 3195.183 s         & 0.015 \\
+FEM\_3D\_thermal2 & 37.211 s         & 1584.650 s         & 0.023 \\
+language          & 22.912 s         & 2242.897 s         & 0.010 \\
+poli\_large       & 13.618 s         & 1722.304 s         & 0.008 \\
+torso3            & 74.194 s         & 4454.936 s         & 0.017 \\ \hline       
+\end{tabular}
+\caption{}
+\label{tab:09}
+\end{center}
+\end{table}
+
+
 \textcolor{red}{\bf Finally, the parallel solving of a linear system can be easy to optimize when the associated matrix is regular. This is unfortunately not the case of many real-world applications. When the matrix has an irregular structure, the amount of communication between processors is not the same. Another important parameter is the size of the matrix bandwidth which has a huge influence on the amount of communications. In this work, we have generated different kinds of matrices in order to analyze different difficulties. With as a large bandwidth as possible involving communications between all processors, which is the most difficult situation, we proposed to use two heuristics. Unfortunately, there is no fast method that optimizes the communication in any situation. For systems of non linear equations, there are different algorithms but most of them consist in linearizing the system of equations. In this case, a linear system needs to be solved. The big interest is that the matrix is the same at each step of the non linear system solving, so the partitioning method which is a time consuming step is performed once only.
 }