From: RCE <cramamonjisoa@bilbo.iut-bm.univ-fcomte.fr>
Date: Tue, 28 Apr 2015 11:36:24 +0000 (+0200)
Subject: RCE : Revue et corrections
X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/rce2015.git/commitdiff_plain/d67fae5d5ed04beaa52fa85856990fe1640cbf75?ds=inline;hp=-c

RCE : Revue et corrections
---

d67fae5d5ed04beaa52fa85856990fe1640cbf75
diff --git a/paper.tex b/paper.tex
index 94bdb91..ce1305d 100644
--- a/paper.tex
+++ b/paper.tex
@@ -342,7 +342,7 @@ architecture scaling up the input matrix size}
 \begin{tabular}{r c }
  \hline  
  Grid & 2x16, 4x8, 4x16 and 8x8\\ %\hline
- Network & N2 : bw=1Gbits/s - lat=\np{5E-5} \\ %\hline
+ Network & N2 : bw=1Gbits/s - lat=5.10$^{-5}$ \\ %\hline
  Input matrix size & N$_{x}$ x N$_{y}$ x N$_{z}$ =150 x 150 x 150\\ %\hline
  - &  N$_{x}$ x N$_{y}$ x N$_{z}$  =170 x 170 x 170    \\ \hline
  \end{tabular}
@@ -363,7 +363,7 @@ the case for the multisplitting method.
 \begin{figure} [ht!]
 \centering
 \includegraphics[width=100mm]{cluster_x_nodes_nx_150_and_nx_170.pdf}
-\caption{Cluster x Nodes NX=150 and NX=170} 
+\caption{Cluster x Nodes N$_{x}$=150 and N$_{x}$=170} 
 %\label{overflow}}
 \end{figure}
 %\end{wrapfigure}
@@ -383,9 +383,9 @@ matrix size.
 \begin{tabular}{r c }
  \hline  
  Grid & 2x16, 4x8\\ %\hline
- Network & N1 : bw=10Gbs-lat=8E-06 \\ %\hline
- - & N2 : bw=1Gbs-lat=5E-05 \\
- Input matrix size & N$_{x}$ =150 x 150 x 150\\ \hline \\
+ Network & N1 : bw=10Gbs-lat=8.10$^{-6}$ \\ %\hline
+ - & N2 : bw=1Gbs-lat=5.10$^{-5}$ \\
+ Input matrix size & N$_{x}$ x N$_{y}$ x N$_{z}$ =150 x 150 x 150\\ \hline \\
  \end{tabular}
 Table 2 : Clusters x Nodes - Networks N1 x N2 \\
 
@@ -403,8 +403,8 @@ Table 2 : Clusters x Nodes - Networks N1 x N2 \\
 %\end{wrapfigure}
 
 The experiments compare the behavior of the algorithms running first on 
-speed inter- cluster network (N1) and a less performant network (N2). 
-The figure 2 shows that end users will gain to reduce the execution time 
+a speed inter- cluster network (N1) and a less performant network (N2). 
+Figure 4 shows that end users will gain to reduce the execution time 
 for both algorithms in using a grid architecture like 4x16 or 8x8: the 
 performance was increased in a factor of 2. The results depict also that 
 when the network speed drops down, the difference between the execution 
@@ -418,9 +418,8 @@ times can reach more than 25\%.
  \hline  
  Grid & 2x16\\ %\hline
  Network & N1 : bw=1Gbs \\ %\hline
- Input matrix size & N$_{x}$ =150 x 150 x 150\\ \hline\\
+ Input matrix size & N$_{x}$ x N$_{y}$ x N$_{z}$ =150 x 150 x 150\\ \hline\\
  \end{tabular}
-
 Table 3 : Network latency impact \\
 
 \end{footnotesize}
@@ -435,12 +434,12 @@ Table 3 : Network latency impact \\
 \end{figure}
 
 
-According the results in table and figure 3, degradation of the network 
+According the results in table and figure 5, degradation of the network 
 latency from 8.10$^{-6}$ to 6.10$^{-5}$ implies an absolute time 
 increase more than 75\% (resp. 82\%) of the execution for the classical 
 GMRES (resp. multisplitting) algorithm. In addition, it appears that the 
 multisplitting method tolerates more the network latency variation with 
-a less rate increase. Consequently, in the worst case (lat=6.10$^{-5
+a less rate increase of the execution time. Consequently, in the worst case (lat=6.10$^{-5
 }$), the execution time for GMRES is almost the double of the time for 
 the multisplitting, even though, the performance was on the same order 
 of magnitude with a latency of 8.10$^{-6}$.