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-% et l'affichage correct des URL (commande \url{http://example.com})
+% et l'affichage correct des UR (commande \url{http://example.com})
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\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 $max_i | A*x-b |_i$.
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
`----
[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
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
