X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/loba-papers.git/blobdiff_plain/e8a50f36912db421cea4c11f504ea9d253a9430f..58583054e42c6065604b04ac3781a45efb869549:/loba-besteffort/loba-besteffort.tex?ds=sidebyside

diff --git a/loba-besteffort/loba-besteffort.tex b/loba-besteffort/loba-besteffort.tex
index b53ffec..23fe6ea 100644
--- a/loba-besteffort/loba-besteffort.tex
+++ b/loba-besteffort/loba-besteffort.tex
@@ -3,9 +3,9 @@
 \usepackage[utf8]{inputenc}
 \usepackage[T1]{fontenc}
 
-\usepackage{newtxtext}
-\usepackage[cmintegrals]{newtxmath}
-%\usepackage{mathptmx,helvet,courier}
+%\usepackage{newtxtext}
+%\usepackage[cmintegrals]{newtxmath}
+\usepackage{mathptmx,helvet,courier}
 
 \usepackage{amsmath}
 \usepackage{graphicx}
@@ -43,10 +43,7 @@
 \ead{arnaud.giersch@femto-st.fr}
 
 \address{FEMTO-ST, University of Franche-ComtÃ©\\
- 19 avenue de MarÃ©chal Juin, BP 527, 90016 Belfort cedex , France\\
-  % Tel.: +123-45-678910\\
-  % Fax: +123-45-678910\\
-}
+ 19 avenue du MarÃ©chal Juin, BP 527, 90016 Belfort cedex, France}
 
 \cortext[cor]{Corresponding author.}
 
@@ -134,20 +131,21 @@ order  to send a  message, a  latency delays  the sending  and according  to the
 network  performance and  the message  size, the  time of  the reception  of the
 message also varies.
 
-In the following of this paper, Section~\ref{BT algo} describes the Bertsekas
-and Tsitsiklis' asynchronous load balancing algorithm. Moreover, we present a
-possible problem in the convergence conditions.  Section~\ref{Best-effort}
-presents the best effort strategy which provides an efficient way to reduce the
-execution times.  This strategy will be compared with other ones, presented in
-Section~\ref{Other}.  In Section~\ref{Virtual load}, the virtual load mechanism
-is proposed.  Simulations allowed to show that both our approaches are valid
-using a quite realistic model detailed in Section~\ref{Simulations}.  Finally we
-give a conclusion and some perspectives to this work.
+In the following of this paper, Section~\ref{sec.bt-algo} describes the
+Bertsekas and Tsitsiklis' asynchronous load balancing algorithm. Moreover, we
+present a possible problem in the convergence conditions.
+Section~\ref{sec.besteffort} presents the best effort strategy which provides an
+efficient way to reduce the execution times.  This strategy will be compared
+with other ones, presented in Section~\ref{sec.other}.  In
+Section~\ref{sec.virtual-load}, the virtual load mechanism is proposed.
+Simulations allowed to show that both our approaches are valid using a quite
+realistic model detailed in Section~\ref{sec.simulations}.  Finally we give a
+conclusion and some perspectives to this work.
 
 
 
 \section{Bertsekas  and Tsitsiklis' asynchronous load balancing algorithm}
-\label{BT algo}
+\label{sec.bt-algo}
 
 In  order  prove  the  convergence  of  asynchronous  iterative  load  balancing
 Bertsekas         and        Tsitsiklis         proposed         a        model
@@ -170,7 +168,7 @@ amount of  load received by processor $j$  from processor $i$ at  time $t$. Then
 the amount of load of processor $i$ at time $t+1$ is given by:
 \begin{equation}
 x_i(t+1)=x_i(t)-\sum_{j\in V(i)} s_{ij}(t) + \sum_{j\in V(i)} r_{ji}(t)
-\label{eq:ping-pong}
+\label{eq.ping-pong}
 \end{equation}
 
 
@@ -193,9 +191,9 @@ x_2(t)=100   \\
 x_3(t)=99.99\\
  x_3^2(t)=99.99\\
 \end{eqnarray*}
-In this case, processor $2$ can  either sends load to processor $1$ or processor
-$3$.   If  it  sends  load  to  processor $1$  it  will  not  satisfy  condition
-(\ref{eq:ping-pong})  because  after the  sending  it  will  be less  loaded  that
+In this case, processor $2$ can either sends load to processor $1$ or processor
+$3$.  If it sends load to processor $1$ it will not satisfy condition
+(\ref{eq.ping-pong}) because after the sending it will be less loaded that
 $x_3^2(t)$.  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.
@@ -209,7 +207,7 @@ that they are sufficient to ensure the convergence of the load-balancing
 algorithm.
 
 \section{Best effort strategy}
-\label{Best-effort}
+\label{sec.besteffort}
 
 In this section we describe a new load-balancing strategy that we call
 \emph{best effort}.  First, we explain the general idea behind this strategy,
@@ -281,12 +279,12 @@ 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 that it's still named $k$ in Sec.~\ref{Results}]{}
+Section~\ref{sec.results}.  The amount of data to send is then $s_{ij}(t) =
+(\bar{x} - x^i_j(t))/k$.
+\FIXME[check that it's still named $k$ in Sec.~\ref{sec.results}]{}
 
 \section{Other strategies}
-\label{Other}
+\label{sec.other}
 
 Another load balancing strategy, working under the same conditions, was
 previously developed by Bahi, Giersch, and Makhoul in
@@ -307,7 +305,7 @@ neighbor.
 
 
 \section{Virtual load}
-\label{Virtual load}
+\label{sec.virtual-load}
 
 In this section,  we present the concept of \emph{virtual load}.  In order to
 use this concept, load balancing messages must be sent using two different kinds
@@ -337,7 +335,7 @@ information of the load they will receive, so they can take in into account.
 \FIXME{describe integer mode}
 
 \section{Simulations}
-\label{Simulations}
+\label{sec.simulations}
 
 In order to test and validate our approaches, we wrote a simulator
 using the SimGrid
@@ -348,13 +346,12 @@ as the initial distribution of load, the interconnection topology, the
 characteristics of the running platform, etc.  Then several metrics
 are issued that permit to compare the strategies.
 
-The simulation model is detailed in the next section (\ref{Sim
-  model}), and the experimental contexts are described in
-section~\ref{Contexts}.  Then the results of the simulations are
-presented in section~\ref{Results}.
+The simulation model is detailed in the next section (\ref{sec.model}), and the
+experimental contexts are described in section~\ref{sec.exp-context}.  Then the
+results of the simulations are presented in section~\ref{sec.results}.
 
 \subsection{Simulation model}
-\label{Sim model}
+\label{sec.model}
 
 In the simulation model the processors exchange messages which are of
 two kinds.  First, there are \emph{control messages} which only carry
@@ -491,10 +488,11 @@ iteratively runs the following operations:
 \end{algorithm}
 
 \paragraph{}\FIXME{ajouter des dÃ©tails sur la gestion de la charge virtuelle ?
-par ex, donner l'idÃ©e gÃ©nÃ©rale de l'implÃ©mentation.  l'idÃ©e gÃ©nÃ©rale est dÃ©ja dÃ©crite en section~\ref{Virtual load}}
+  par ex, donner l'idÃ©e gÃ©nÃ©rale de l'implÃ©mentation.  l'idÃ©e gÃ©nÃ©rale est dÃ©ja
+  dÃ©crite en section~\ref{sec.virtual-load}}
 
 \subsection{Experimental contexts}
-\label{Contexts}
+\label{sec.exp-context}
 
 In order to assess the performances of our algorithms, we ran our
 simulator with various parameters, and extracted several metrics, that
@@ -602,6 +600,7 @@ Anyway, all these the experiments represent more than 240 hours of computing
 time.
 
 \subsubsection{Metrics}
+\label{sec.metrics}
 
 In order to evaluate and compare the different load balancing strategies we had
 to define several metrics.  Our goal, when choosing these metrics, was to have
@@ -643,7 +642,7 @@ With these constraints in mind, we defined the following metrics:
 
 
 \subsection{Experimental results}
-\label{Results}
+\label{sec.results}
 
 In this section, the results for the different simulations will be presented,
 and we'll try to explain our observations.
@@ -660,7 +659,7 @@ Nevertheless their relative performances remain generally identical.
 This suggests that the relative performances of the different strategies are not
 influenced by the characteristics of the physical platform.  The differences in
 the convergence times can be explained by the fact that on the grid platforms,
-distant sites are interconnected by links of smaller bandwith.
+distant sites are interconnected by links of smaller bandwidth.
 
 Therefore, in the following, we'll only discuss the results for the grid
 platforms.
@@ -699,7 +698,7 @@ initially on an only node, while the results on figure~\ref{fig.resultsN} are
 when the load to balance is initially randomly distributed over all nodes.
 
 On both figures, the computation/communication cost ratio is $10/1$ on the left
-column, and $1/10$ on the right column.  With a computatio/communication cost
+column, and $1/10$ on the right column.  With a computation/communication cost
 ratio of $1/1$ the results are just between these two extrema, and definitely
 don't give additional information, so we chose not to show them here.
 
@@ -707,62 +706,55 @@ On each of the figures~\ref{fig.results1} and~\ref{fig.resultsN}, the results
 are given for the process topology being, from top to bottom, a line, a torus or
 an hypercube.
 
-\FIXME{explain how to read the graphs}
+Finally, on the graphs, the vertical bars show the measured times for each of
+the algorithms.  These measured times are, from bottom to top, the average idle
+time, the average convergence date, and the maximum convergence date (see
+Section~\ref{sec.metrics}).  The measurements are repeated for the different
+platform sizes.  Some bars are missing, specially for large platforms.  This is
+either because the algorithm did not reach the convergence state in the
+allocated time, or because we simply decided not to run it.
 
-each bar -> times for an algorithm
-recall the different times
-no bar -> not run or did not converge in allocated time
+\FIXME{annoncer le plan de la suite}
 
-repeated for the different platform sizes.
+\subsubsection{The \emph{best effort} strategy}
 
-\FIXME{donner les premiÃ¨res conclusions, annoncer le plan de la suite}
+Looking at the graph on figure~\ref{fig.results1}, we can see that the
+\emph{best effort} strategy is not too bad.
+
+\FIXME{donner les premiÃ¨res conclusions}
+\FIXME{comparer be/makhoul -> be tient la route (parler du cas rÃ©el uniquement)}
 
 \subsubsection{With the virtual load extension}
 
+\FIXME{valider l'extension virtual load -> c'est 'achement bien}
+
 \subsubsection{The $k$ parameter}
 
-\subsubsection{With an initial random repartition,  and larger platforms}
+\FIXME{proposer le -k -> Ã§a peut aider dans certains cas}
+
+\subsubsection{With an initial random distribution, and larger platforms}
+
+\FIXME{dire quoi ici ?}
 
 \subsubsection{With integer load}
 
+\FIXME{conclure avec la version entiÃ¨re -> on n'a pas l'effet d'escalier !}
+
 \FIXME{what about the amount of data?}
 
-\begin{itshape}
-\FIXME{remove that part}
-Dans cet ordre:
-...
-- comparer be/makhoul -> be tient la route
-        -> en rÃ©el uniquement
-- valider l'extension virtual load -> c'est 'achement bien
-- proposer le -k -> Ã§a peut aider dans certains cas
-- conclure avec la version entiÃ¨re -> on n'a pas l'effet d'escalier !
-Q: comment inclure les types/tailles de platesformes ?
-Q: comment faire des moyennes ?
-Q: comment introduire les distrib 1/N ?
-...
-
-On constate quoi (vÃ©rifier avec les chiffres)?
+\FIXME{On constate quoi (vÃ©rifier avec les chiffres)?
 \begin{itemize}
 \item cluster ou grid, entier ou rÃ©el, ne font pas de grosses diffÃ©rences
-
 \item bookkeeping? amÃ©liore souvent les choses, parfois au prix d'un retard au dÃ©marrage
-
 \item makhoul? se fait battre sur les grosses plateformes
-
 \item taille de plateforme?
-
 \item ratio comp/comm?
-
 \item option $k$? peut-Ãªtre intÃ©ressant sur des plateformes fortement interconnectÃ©es (hypercube)
-
 \item volume de comm? souvent, besteffort/plain en fait plus. pourquoi?
-
 \item rÃ©partition initiale de la charge ?
-
 \item integer mode sur topo. line n'a jamais fini en plain? vÃ©rifier si ce n'est
   pas Ã  cause de l'effet d'escalier que bk est capable de gommer.
-
-\end{itemize}
+\end{itemize}}
 
 % On veut montrer quoi ? :
 
@@ -789,13 +781,12 @@ On constate quoi (vÃ©rifier avec les chiffres)?
 % Prendre un rÃ©seau hÃ©tÃ©rogÃ¨ne et rendre processeur homogÃ¨ne
 
 % Taille : 10 100 trÃ¨s gros
-\end{itshape}
 
 \section{Conclusion and perspectives}
 
 \FIXME{conclude!}
 
-\section*{Acknowledgements}
+\section*{Acknowledgments}
 
 Computations have been performed on the supercomputer facilities of the
 MÃ©socentre de calcul de Franche-ComtÃ©.
@@ -813,7 +804,8 @@ MÃ©socentre de calcul de Franche-ComtÃ©.
 %%% ispell-local-dictionary: "american"
 %%% End:
 
-% LocalWords:  RaphaÃ«l Couturier Arnaud Giersch Abderrahmane Sider Franche ij
-% LocalWords:  Bertsekas Tsitsiklis SimGrid DASUD ComtÃ© BÃ©jaÃ¯a asynchronism ji
-% LocalWords:  ik isend irecv CortÃ©s et al chan ctrl fifo Makhoul GFlop xml pre
-% LocalWords:  FEMTO Makhoul's fca bdee cdde Contassot Vivier underlaid
+% LocalWords:  RaphaÃ«l Couturier Arnaud Giersch Franche ij Bertsekas Tsitsiklis
+% LocalWords:  SimGrid DASUD ComtÃ© asynchronism ji ik isend irecv CortÃ©s et al
+% LocalWords:  chan ctrl fifo Makhoul GFlop xml pre FEMTO Makhoul's fca bdee
+% LocalWords:  cdde Contassot Vivier underlaid du de MarÃ©chal Juin cedex calcul
+% LocalWords:  biblio
