X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/rce2015.git/blobdiff_plain/34ef1c761f30fa1a22267a93d9aeaabb90869ada..2e01ef1240fcecca4313cea0cb013a8c0b09f9f5:/paper.tex diff --git a/paper.tex b/paper.tex index beb3140..8126583 100644 --- a/paper.tex +++ b/paper.tex @@ -407,10 +407,10 @@ in which several clusters are geographically distant, so there are intra and inter-cluster communications. In the following, these parameters are described: \begin{itemize} - \item hostfile: hosts description file. + \item hostfile: hosts description file, \item platform: file describing the platform architecture: clusters (CPU power, \dots{}), intra cluster network description, inter cluster network (bandwidth $bw$, -latency $lat$, \dots{}). +latency $lat$, \dots{}), \item archi : grid computational description (number of clusters, number of nodes/processors in each cluster). \end{itemize} @@ -485,7 +485,7 @@ results comparison and analysis. In the scope of this study, we retain on the one hand the algorithm execution mode (synchronous and asynchronous) and on the other hand the execution time and the number of iterations to reach the convergence. \\ -\textbf{Step 4 }: Set up the different grid testbed environments that will be +\textbf{Step 4}: Set up the different grid testbed environments that will be simulated in the simulator tool to run the program. The following architectures have been configured in SimGrid : 2$\times$16, 4$\times$8, 4$\times$16, 8$\times$8 and 2$\times$50. The first number represents the number of clusters in the grid and the second number represents @@ -494,8 +494,8 @@ designed to operate with a bandwidth equals to 10Gbits (resp. 1Gbits/s) and a latency of 8.10$^{-6}$ seconds (resp. 5.10$^{-5}$) for the intra-clusters links (resp. inter-clusters backbone links). \\ -\LZK{Il me semble que le bw et lat des deux réseaux varient dans les expés d'une simu à l'autre. On vire la dernière phrase?} -\RC{il me semble qu'on peut laisser ca} +%\LZK{Il me semble que le bw et lat des deux réseaux varient dans les expés d'une simu à l'autre. On vire la dernière phrase?} +%\RC{il me semble qu'on peut laisser ca} \textbf{Step 5}: Conduct an extensive and comprehensive testings within these configurations by varying the key parameters, especially @@ -644,9 +644,9 @@ the network speed drops down (variation of 12.5\%), the difference between t \begin{figure} [htbp] \centering \includegraphics[width=100mm]{cluster_x_nodes_n1_x_n2.pdf} -\caption{Various grid configurations with networks N1 vs N2 -\AG{\np{8E-6}, \np{5E-6} au lieu de 8E-6, 5E-6}} -\RCE{Corrige} +\caption{Various grid configurations with networks N1 vs N2} +%\AG{\np{8E-6}, \np{5E-6} au lieu de 8E-6, 5E-6}} +%\RCE{Corrige} \label{fig:02} \end{figure} %\end{wrapfigure} @@ -670,18 +670,19 @@ the network speed drops down (variation of 12.5\%), the difference between t \begin{figure} [htbp] \centering \includegraphics[width=100mm]{network_latency_impact_on_execution_time.pdf} -\caption{Network latency impacts on execution time -\AG{\np{E-6}}} +\caption{Network latency impacts on execution time} +%\AG{\np{E-6}}} \label{fig:03} \end{figure} -According to the results of Figure~\ref{fig:03}, a degradation of the network -latency from $8.10^{-6}$ to $6.10^{-5}$ implies an absolute time increase of -more than $75\%$ (resp. $82\%$) of the execution for the classical GMRES -(resp. Krylov multisplitting) algorithm which means that the GMRES seems tolerate more the network latency variation with a less rate increase of the execution time. However, the execution time factor between the two algorithms varies from 2.2 to 1.5 times with a network latency decreasing from $8.10^{-6}$ to $6.10^{-5}$. +In Table~\ref{tab:03}, parameters for the influence of the network latency are +reported. According to the results of Figure~\ref{fig:03}, a degradation of the +network latency from $8.10^{-6}$ to $6.10^{-5}$ implies an absolute time +increase of more than $75\%$ (resp. $82\%$) of the execution for the classical +GMRES (resp. Krylov multisplitting) algorithm. The execution time factor +between the two algorithms varies from 2.2 to 1.5 times with a network latency +decreasing from $8.10^{-6}$ to $6.10^{-5}$. -\RC{Les 2 précédentes phrases me semblent en contradiction....} -\RCE{Reformule} \subsubsection{Network bandwidth impacts on performance} \ \\ @@ -694,8 +695,9 @@ more than $75\%$ (resp. $82\%$) of the execution for the classical GMRES & $lat$= 5.10$^{-5}$ second \\ Input matrix size & $N_{x} \times N_{y} \times N_{z} =150 \times 150 \times 150$\\ \hline \\ \end{tabular} -\caption{Test conditions: Network bandwidth impacts\RC{Qu'est ce qui varie ici? Il n'y a pas de variation dans le tableau}} -\RCE{C est le bw} +\caption{Test conditions: Network bandwidth impacts} +% \RC{Qu'est ce qui varie ici? Il n'y a pas de variation dans le tableau} +%\RCE{C est le bw} \label{tab:04} \end{table} @@ -723,7 +725,7 @@ of $40\%$ which is only around $24\%$ for the classical GMRES. \hline Grid Architecture & 4 $\times$ 8\\ %\hline Inter Network & $bw$=1Gbs - $lat$=5.10$^{-5}$ \\ - Input matrix size & $N_{x} \times N_{y} \times N_{z}$ = From 40$^{3}$ to 200$^{3}$\\ \hline + Input matrix size & $N_{x} \times N_{y} \times N_{z}$ = From 50$^{3}$ to 190$^{3}$\\ \hline \end{tabular} \caption{Test conditions: Input matrix size impacts} \label{tab:05} @@ -737,20 +739,15 @@ of $40\%$ which is only around $24\%$ for the classical GMRES. \label{fig:05} \end{figure} -In these experiments, the input matrix size has been set from $N_{x} = N_{y} -= N_{z} = 40$ to $200$ side elements that is from $40^{3} = 64.000$ to $200^{3} -= 8,000,000$ points. Obviously, as shown in Figure~\ref{fig:05}, the execution -time for both algorithms increases when the input matrix size also increases. -But the interesting results are: -\begin{enumerate} - \item the important increase ($10$ times) of the number of iterations needed to - reach the convergence for the classical GMRES algorithm particularly, when the matrix size - go beyond $N_{x}=150$; \RC{C'est toujours pas clair... ok le nommbre d'itérations est 10 fois plus long mais la suite de la phrase ne veut rien dire} - \RCE{Le nombre d'iterations augmente de 10 fois, cela surtout a partir de N=150} - -\item the classical GMRES execution time is almost the double for $N_{x}=140$ - compared with the Krylov multisplitting method. -\end{enumerate} +In these experiments, the input matrix size has been set from $50^3$ to +$190^3$. Obviously, as shown in Figure~\ref{fig:05}, the execution time for both +algorithms increases when the input matrix size also increases. For all problem +sizes, GMRES is always slower than the Krylov multisplitting. Moreover, for this +benchmark, it seems that the greater the problem size is, the bigger the ratio +between both algorithm execution times is. We can also observ that for some +problem sizes, the Krylov multisplitting convergence varies quite a +lot. Consequently the execution times in that cases also varies. + These findings may help a lot end users to setup the best and the optimal targeted environment for the application deployment when focusing on the problem