petites remarques

diff --git a/hpcc.tex b/hpcc.tex
index 8f0549f876489226238e4325e920376953897511..1e90946f706b73b3808b1bce4dbd397185e8ecf9 100644 (file)
--- a/hpcc.tex
+++ b/hpcc.tex
@@ -10,7 +10,7 @@
 \usepackage{graphicx}
 \usepackage[american]{babel}
 % Extension pour les liens intra-documents (tagged PDF)
 \usepackage{graphicx}
 \usepackage[american]{babel}
 % Extension pour les liens intra-documents (tagged PDF)

-% et l'affichage correct des URL (commande \url{http://example.com})
+% et l'affichage correct des UR (commande \url{http://example.com})

 %\usepackage{hyperref}
 
 \usepackage{url}
 %\usepackage{hyperref}
 
 \usepackage{url}


@@ -420,7 +420,7 @@ condition is satisfied
 \end{equation*}
 where $\MI$ is the maximum number of outer iterations and $\epsilon$ is the
 tolerance threshold of the error computed between two successive local solution
 \end{equation*}
 where $\MI$ is the maximum number of outer iterations and $\epsilon$ is the
 tolerance threshold of the error computed between two successive local solution

-$X_\ell^k$ and $X_\ell^{k+1}$.
+$X_\ell^k$ and $X_\ell^{k+1}$. It should be noted that with asynchronous iterative algorithms, we cannot use a classical norm (which would require to synchronize all processors), such as $\|X_\ell^k - X_\ell^{k+1}\|_{2}$ for example. Nevertheless, in our experiments, we check that the final result is correct, for this we compute the precision with $max_i | A*x-b |_i$.

 
 
 
 
 
 


@@ -683,7 +683,7 @@ stable even if the residual error precision varies from \np{E-5} to \np{E-9}. By
 increasing the matrix size up to $100^3$ elements, it was necessary to increase the
 CPU power by \np[\%]{50} to \np[GFlops]{1.5} to get the algorithm convergence and the same order of asynchronous mode efficiency.  Maintaining  a relative gain of $2.5$ and such processor power but increasing network throughput inter cluster up to \np[Mbit/s]{50},  is obtained with
 high external precision of \np{E-11} for a matrix size from $110^3$ to $150^3$ side
 increasing the matrix size up to $100^3$ elements, it was necessary to increase the
 CPU power by \np[\%]{50} to \np[GFlops]{1.5} to get the algorithm convergence and the same order of asynchronous mode efficiency.  Maintaining  a relative gain of $2.5$ and such processor power but increasing network throughput inter cluster up to \np[Mbit/s]{50},  is obtained with
 high external precision of \np{E-11} for a matrix size from $110^3$ to $150^3$ side

-elements.
+elements. 

 
 %For the 3 clusters architecture including a total of 100 hosts,
 %Table~\ref{tab.cluster.3x33} shows that it was difficult to have a combination
 
 %For the 3 clusters architecture including a total of 100 hosts,
 %Table~\ref{tab.cluster.3x33} shows that it was difficult to have a combination

diff --git a/hpcc2014_reviews.txt b/hpcc2014_reviews.txt
index ff8faf8a8edece1f03a6e17e53b5c042df61fd06..2c5393aa8d4fe7c0ba4e842c844070201fd31af8 100644 (file)
--- a/hpcc2014_reviews.txt
+++ b/hpcc2014_reviews.txt
@@ -256,7 +256,9 @@ AUTHORS: Charles Emile Ramamonjisoa, David Laiymani, Arnaud Giersch,
 `----
 
 [RCE] ??
 `----
 
 [RCE] ??

- 
+[RC] En gros il nous critique car on a pris un problème trop simple.
+                On le sait, mais on fait de l'asynchrone. Donc on ne répondra pas à 
+                cette remarque. 

 
 ,----
 | 3) This is somewhat of a minor point, but I did not see an explicit
 
 ,----
 | 3) This is somewhat of a minor point, but I did not see an explicit


@@ -281,6 +283,7 @@ AUTHORS: Charles Emile Ramamonjisoa, David Laiymani, Arnaud Giersch,
       convergé: (k==MaxIter)or(X^k−X^k+1)<=epsilon, X sous-vecteur
       local de la solution et epsilon est la outer precision et donc
       la précision donnée dans la table I. 
       convergé: (k==MaxIter)or(X^k−X^k+1)<=epsilon, X sous-vecteur
       local de la solution et epsilon est la outer precision et donc
       la précision donnée dans la table I. 

+[RC]   J'ai ajouté un truc là dessus, section IV A

 
 ,----
 | 4) Typical latencies within clusters are on the order of a
 
 ,----
 | 4) Typical latencies within clusters are on the order of a