From: jccharr Date: Wed, 29 Oct 2014 16:01:29 +0000 (+0100) Subject: text for curves at the end of sction 5 X-Git-Tag: pdsec15_submission~87 X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/mpi-energy2.git/commitdiff_plain/0ae1cf0b7fb7410bed4b0f50cbbf47fb66a6fc39 text for curves at the end of sction 5 --- diff --git a/Heter_paper.tex b/Heter_paper.tex index 11e9475..e9f6b67 100644 --- a/Heter_paper.tex +++ b/Heter_paper.tex @@ -352,10 +352,19 @@ nodes having the characteristics presented in table~(\ref{table:platform}), it takes \np[ms]{0.04} on average for 4 nodes and \np[ms]{0.15} on average for 144 nodes. The algorithm complexity is $O(F\cdot (N \cdot4) )$, where $F$ is the number of iterations and $N$ is the number of computing nodes. The algorithm -needs on average from 12 to 20 iterations to selects the best vector of frequency scaling factors that give the results of the next section. \textbf{put the lst paragraph in experiments} - +needs on average from 12 to 20 iterations to selects the best vector of frequency scaling factors that give the results of the next section. +Therefore, there is a small distance between the energy and +the performance curves in a homogeneous cluster compare to heterogeneous one, for example see the figure(\ref{fig:r1}) and figure(\ref{fig:r2}) . Then the +algorithm starts to search for the optimal vector of the frequency scaling factors from the selected initial +frequencies until all node reach their minimum frequencies. +\begin{figure}[t] + \centering + \includegraphics[scale=0.5]{fig/start_freq} + \caption{Selecting the initial frequencies} + \label{fig:st_freq} +\end{figure}