Updated script.r

[loba-papers.git] / supercomp11 / supercomp11.tex

diff --git a/supercomp11/supercomp11.tex b/supercomp11/supercomp11.tex
index 2f2dd31bc46905d59c46caae3c0a96782fc50c34..c6e904a475540a83d89f4ffa6990c5ee514117f4 100644 (file)
--- a/supercomp11/supercomp11.tex
+++ b/supercomp11/supercomp11.tex
@@ -14,8 +14,11 @@
   \begin{tabular}[t]{@{}l@{:~}l@{}}}{%
   \end{tabular}}
 
   \begin{tabular}[t]{@{}l@{:~}l@{}}}{%
   \end{tabular}}
 

-\newcommand{\FIXME}[1]{%
-  \textbf{$\triangleright$\marginpar{\textbf{[FIXME]}}~#1}}
+\newcommand{\FIXMEmargin}[1]{%
+  \marginpar{\textbf{[FIXME]} {\footnotesize #1}}}
+\newcommand{\FIXME}[2][]{%
+  \ifx #2\relax\relax \FIXMEmargin{#1}%
+  \else \textbf{$\triangleright$\FIXMEmargin{#1}~#2}\fi}

 
 \newcommand{\VAR}[1]{\textit{#1}}
 
 
 \newcommand{\VAR}[1]{\textit{#1}}
 


@@ -85,7 +88,7 @@ been extended by many authors. For example, Cortés et al., with
 DASUD~\cite{cortes+ripoll+cedo+al.2002.asynchronous}, propose a
 version working with integer load.  This work was later generalized by
 the same authors in \cite{cedo+cortes+ripoll+al.2007.convergence}.
 DASUD~\cite{cortes+ripoll+cedo+al.2002.asynchronous}, propose a
 version working with integer load.  This work was later generalized by
 the same authors in \cite{cedo+cortes+ripoll+al.2007.convergence}.

-\FIXME{Rajouter des choses ici.}
+\FIXME{Rajouter des choses ici.  Lesquelles ?}

 
 Although  the Bertsekas  and Tsitsiklis'  algorithm describes  the  condition to
 ensure the convergence,  there is no indication or  strategy to really implement
 
 Although  the Bertsekas  and Tsitsiklis'  algorithm describes  the  condition to
 ensure the convergence,  there is no indication or  strategy to really implement


@@ -186,11 +189,14 @@ $3$.   If  it  sends  load  to  processor $1$  it  will  not  satisfy  condition
 $x_3^2(t)$.  So we consider that the \emph{ping-pong} condition is probably to
 strong. Currently, we did not try to make another convergence proof without this
 condition or with a weaker condition.
 $x_3^2(t)$.  So we consider that the \emph{ping-pong} condition is probably to
 strong. Currently, we did not try to make another convergence proof without this
 condition or with a weaker condition.

-%
-\FIXME{Develop: We have the feeling that such a weaker condition
-  exists, because (it's not a proof, but) we have never seen any
-  scenario that is not leading to convergence, even with LB-strategies
-  that are not fulfilling these two conditions.}
+
+Nevertheless, we conjecture that such a weaker condition exists.  In fact, we
+have never seen any scenario that is not leading to convergence, even with
+load-balancing strategies that are not exactly fulfilling these two conditions.
+
+It may be the subject of future work to express weaker conditions, and to prove
+that they are sufficient to ensure the convergence of the load-balancing
+algorithm.

 
 \section{Best effort strategy}
 \label{Best-effort}
 
 \section{Best effort strategy}
 \label{Best-effort}


@@ -260,45 +266,35 @@ several of its neighbors, and then is temporary going off the equilibrium state.
 This is particularly true with strongly connected applications.
 
 In order to reduce this effect, we add the ability to level the amount to send.
 This is particularly true with strongly connected applications.
 
 In order to reduce this effect, we add the ability to level the amount to send.

-The idea, here, is to make smaller steps toward the equilibrium, such as a
+The idea, here, is to make smaller steps toward the equilibrium, such that a

 potentially wrong decision has a lower impact.
 
 Concretely, once $s_{ij}$ has been evaluated as before, it is simply divided by
 some configurable factor.  That's what we named the ``parameter $k$'' in
 Section~\ref{Results}.  The amount of data to send is then $s_{ij}(t) = (\bar{x}
 - x^i_j(t))/k$.
 potentially wrong decision has a lower impact.
 
 Concretely, once $s_{ij}$ has been evaluated as before, it is simply divided by
 some configurable factor.  That's what we named the ``parameter $k$'' in
 Section~\ref{Results}.  The amount of data to send is then $s_{ij}(t) = (\bar{x}
 - x^i_j(t))/k$.

-\FIXME{check the name ($k$)}
+\FIXME[check that it's still named $k$ in Sec.~\ref{Results}]{}

 
 \section{Other strategies}
 \label{Other}
 
 
 \section{Other strategies}
 \label{Other}
 

-\FIXME{Réécrire en anglais.}
-
-% \FIXME{faut-il décrire les stratégies makhoul et simple ?}
-
-% \paragraph{simple} Tentative de respecter simplement les conditions de Bertsekas.
-% Parmi les voisins moins chargés que soi, on sélectionne :
-% \begin{itemize}
-% \item un des moins chargés (vmin) ;
-% \item un des plus chargés (vmax),
-% \end{itemize}
-% puis on équilibre avec vmin en s'assurant que notre charge reste
-% toujours supérieure à celle de vmin et à celle de vmax.
-
-% On envoie donc (avec "self" pour soi-même) :
-% \[
-%     \min\left(\frac{load(self) - load(vmin)}{2}, load(self) - load(vmax)\right)
-% \]
+Another load balancing strategy, working under the same conditions, was
+previously developed by Bahi, Giersch, and Makhoul in
+\cite{bahi+giersch+makhoul.2008.scalable}.  In order to assess the performances
+of the new \emph{best effort}, we naturally chose to compare it to this anterior
+work.  More precisely, we will use the algorithm~2 from
+\cite{bahi+giersch+makhoul.2008.scalable} and, in the following, we will
+reference it under the name of Makhoul's.

 
 

-\paragraph{makhoul} Ordonne les voisins du moins chargé au plus chargé
-puis calcule les différences de charge entre soi-même et chacun des
-voisins.
+Here is an outline of the Makhoul's algorithm.  When a given node needs to take
+a load balancing decision, it starts by sorting its neighbors by increasing
+order of their load.  Then, it computes the difference between its own load, and
+the load of each of its neighbors.  Finally, taking the neighbors following the
+order defined before, the amount of load to send $s_{ij}$ is computed as
+$1/(N+1)$ of the load difference, with $N$ being the number of neighbors.  This
+process continues as long as the node is more loaded than the considered
+neighbor.

 
 

-Ensuite, pour chaque voisin, dans l'ordre, et tant qu'on reste plus
-chargé que le voisin en question, on lui envoie 1/(N+1) de la
-différence calculée au départ, avec N le nombre de voisins.
-
-C'est l'algorithme~2 dans~\cite{bahi+giersch+makhoul.2008.scalable}.

 
 \section{Virtual load}
 \label{Virtual load}
 
 \section{Virtual load}
 \label{Virtual load}


@@ -482,7 +478,8 @@ actual source code that was used for the experiments%
 available at
 \url{http://info.iut-bm.univ-fcomte.fr/staff/giersch/software/loba.tar.gz}.
 
 available at
 \url{http://info.iut-bm.univ-fcomte.fr/staff/giersch/software/loba.tar.gz}.
 

-\FIXME{ajouter des détails sur la gestion de la charge virtuelle ?}
+\FIXME{ajouter des détails sur la gestion de la charge virtuelle ?
+par ex, donner l'idée générale de l'implémentation.  l'idée générale est déja décrite en section~\ref{Virtual load}}

 
 \subsection{Experimental contexts}
 \label{Contexts}
 
 \subsection{Experimental contexts}
 \label{Contexts}


@@ -520,7 +517,8 @@ number of computing iterations (2000 in our case).
 Note that this convergence detection was implemented in a centralized manner.
 This is easy to do within the simulator, but it's obviously not realistic.  In a
 real application we would have chosen a decentralized convergence detection
 Note that this convergence detection was implemented in a centralized manner.
 This is easy to do within the simulator, but it's obviously not realistic.  In a
 real application we would have chosen a decentralized convergence detection

-algorithm, like the one described in \cite{10.1109/TPDS.2005.2}.
+algorithm, like the one described by Bahi, Contassot-Vivier, Couturier, and
+Vernier in \cite{10.1109/TPDS.2005.2}.

 
 \paragraph{Platforms}
 
 
 \paragraph{Platforms}
 


@@ -635,8 +633,44 @@ With these constraints in mind, we defined the following metrics:
 \subsection{Validation of our approaches}
 \label{Results}
 
 \subsection{Validation of our approaches}
 \label{Results}
 

+Dans cet ordre:
+...
+- comparer be/makhoul -> be tient la route
+        -> en réel uniquement
+
+- valider l'extension virtual load -> c'est 'achement bien
+- proposer le -k -> ça peut aider dans certains cas
+- conclure avec la version entière -> on n'a pas l'effet d'escalier !
+Q: comment inclure les types/tailles de platesformes ?
+Q: comment faire des moyennes ?
+...
+
+On constate quoi (vérifier avec les chiffres)?
+\begin{itemize}
+\item cluster ou grid, entier ou réel, ne font pas de grosses différences
+
+\item bookkeeping? améliore souvent les choses, parfois au prix d'un retard au démarrage

 
 

+\item makhoul? se fait battre sur les grosses plateformes
+
+\item taille de plateforme?
+
+\item ratio comp/comm?
+
+\item option $k$? peut-être intéressant sur des plateformes fortement interconnectées (hypercube)
+
+\item volume de comm? souvent, besteffort/plain en fait plus. pourquoi?
+
+\item répartition initiale de la charge ?
+
+\item integer mode sur topo. line n'a jamais fini en plain? vérifier si ce n'est
+  pas à cause de l'effet d'escalier que bk est capable de gommer.
+
+\end{itemize}
+
+\begin{itshape}

 On veut montrer quoi ? :
 On veut montrer quoi ? :

+\FIXME{remove that part}

 
 1) best plus rapide que les autres (simple, makhoul)
 2) avantage virtual load
 
 1) best plus rapide que les autres (simple, makhoul)
 2) avantage virtual load


@@ -648,7 +682,6 @@ Topologies variées
 Simulation avec temps définies assez long et on mesure la qualité avec : volume de calcul effectué, volume de données échangées
 Mais aussi simulation avec temps court qui montre que seul best converge
 
 Simulation avec temps définies assez long et on mesure la qualité avec : volume de calcul effectué, volume de données échangées
 Mais aussi simulation avec temps court qui montre que seul best converge
 

-

 Expés avec ratio calcul/comm rapide et lent
 
 Quelques expés avec charge initiale aléatoire plutot que sur le premier proc
 Expés avec ratio calcul/comm rapide et lent
 
 Quelques expés avec charge initiale aléatoire plutot que sur le premier proc


@@ -662,14 +695,18 @@ On ne tient pas compte de la vitesse des liens donc on la considère homogène
 Prendre un réseau hétérogène et rendre processeur homogène
 
 Taille : 10 100 très gros
 Prendre un réseau hétérogène et rendre processeur homogène
 
 Taille : 10 100 très gros

+\end{itshape}

 
 \section{Conclusion and perspectives}
 
 
 \section{Conclusion and perspectives}
 

+\FIXME{conclude!}
+

 \begin{acknowledgements}
   Computations have been performed on the supercomputer facilities of
   the Mésocentre de calcul de Franche-Comté.
 \end{acknowledgements}
 
 \begin{acknowledgements}
   Computations have been performed on the supercomputer facilities of
   the Mésocentre de calcul de Franche-Comté.
 \end{acknowledgements}
 

+\FIXME{find and add more references}

 \bibliographystyle{spmpsci}
 \bibliography{biblio}
 
 \bibliographystyle{spmpsci}
 \bibliography{biblio}
 


@@ -684,4 +721,5 @@ Taille : 10 100 très gros
 
 % LocalWords:  Raphaël Couturier Arnaud Giersch Abderrahmane Sider Franche ij
 % LocalWords:  Bertsekas Tsitsiklis SimGrid DASUD Comté Béjaïa asynchronism ji
 
 % LocalWords:  Raphaël Couturier Arnaud Giersch Abderrahmane Sider Franche ij
 % LocalWords:  Bertsekas Tsitsiklis SimGrid DASUD Comté Béjaïa asynchronism ji

-% LocalWords:  ik isend irecv Cortés et al chan ctrl fifo Makhoul GFlop xml
+% LocalWords:  ik isend irecv Cortés et al chan ctrl fifo Makhoul GFlop xml pre
+% LocalWords:  FEMTO Makhoul's fca bdee cdde Contassot Vivier underlaid