+
+\label{sec:neurad_xp}
+
+\subsubsection{Conditions}
+\label{sec:neurad_cond}
+
+
+The evaluation of the execution of the Neurad application on XWCH was
+composed as follows. The size of the input data is about 2.4Gb. This
+amount of data can be divided into 25 parts – otherwise, data noise
+appears and will disturb the learning. We have used 25 computers (XWCH
+workers) to execute this part of the application. This generates input
+data parts of about 15Mb (in a compressed format). The output data,
+which are retrieved after the process, are about 30Kb for each part. We
+used two distincts deployments of XWCH. In the first one, the XWCH
+coordinator and the warehouses were situated in Geneva, Switzerland
+while the workers were running in the same local cluster in Belfort,
+France. The second deployment is a local deployment where both
+coordinator, warehouses and workers were in the same local cluster.
+During the day these machines were used by students of the Computer
+Science Department of the IUT of Belfort.
+
+We have furthermore compared the execution of the Neurad application
+with and without the XWCH platform in order to measure the overhead
+induced by the use of the platform. By "without XWCH" we mean that the
+testbed consists only in workers deployed with their respective data by
+the use of shell scripts. No specific middleware was used and the
+workers were in the same local cluster.
+
+Five computation precisions were used: $1e^{-1}$, $0.75e^{-1}$, $0.50e^{-1}$, $0.25e^{-1}$ and $1e^{-2}$.
+
+
+\subsubsection{Results}
+\label{sec:neurad_result}
+
+
+In these experiments, we measured the same steps on both kinds of
+executions. The steps consist of sending of local data and the
+executable, the learning process, and retrieving the result. Table
+\ref{tab:neurad_res} presents the execution times of the Neurad
+application on 25 machines with XWCH (local and distributed deployment)
+and without XWCH.
+
+
+\begin{table}[h!]
+ \centering
+ \begin{tabular}[h!]{|c|c|c|c|c|}
+ \hline
+ Precision & 1 machine & Without XWCH & With XWCH & With local XWCH\\
+ \hline
+ $1e^{-1}$ & 5190 & 558 & 759 & 629\\
+ $0.75e^{-1}$ & 6307 & 792 & 1298 & 801 \\
+ $0.50e^{-1}$ & 7487 & 792 & 1010 & 844 \\
+ $0.25e^{-1}$ & 7787 & 791 & 1000 & 852\\
+ $1e^{-2}$ & 11030 & 1035 & 1447 & 1108 \\
+ \hline
+ \end{tabular}
+\caption{Execution time in seconds of the Neurad application, with and without using the XWCH platform}
+ \label{tab:neurad_res}
+\end{table}
+
+%\begin{table}[ht]
+% \centering
+% \begin{tabular}[h]{|c|c|c|}
+% \hline
+% Precision & Without XWCH & With XWCH \\
+% \hline
+% $1e^{-1}$ & $558$s & $759$s\\
+% \hline
+% \end{tabular}
+% \caption{Execution time in seconds of Neurad application, with and without using XtremWeb-CH platform}
+% \label{tab:neurad_res}
+%\end{table}
+
+
+These experiments show that the overhead induced by the use of the XWCH
+platform is about $34\%$ in the distributed deployment and about $7\%$
+in the local deployment. For this last one, the overhead is very acceptable regarding to the benefits of the platform.
+
+Now, in the distributed deployment the overhead is also acceptable and can be explained by
+different factors. First, we point out that the conditions of executions
+are not really identical between with and without XWCH. For this last
+one, though the same steps were done, all transfer processes are inside
+a local cluster with a high bandwidth and a low latency. Whereas when
+using XWCH, all transfer processes (between datawarehouses, workers, and
+the coordinator) used a wide network area with a smaller bandwidth.
+
+In addition, in executions without XWCH, all the machines started
+immediately the computation, whereas when using the XWCH platform, a
+latency is introduced by the fact that a task starts on a machine, only
+when this one requests a task.
+
+These experiments underline that deploying a local coordinator and one
+or more warehouses near a cluster of workers can enhance computations
+and platform performances. They also show a limited overhead due to the
+use of the platform.
+
+
+\end{document}
+
+
+