X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/mpi-energy2.git/blobdiff_plain/c6d8bdf3c2cf4d02b1a524acd47f59934bcdc35e..82cc99317783214c1562e1d5e39076d77770ad60:/mpi-energy2-extension/Heter_paper.tex?ds=sidebyside

diff --git a/mpi-energy2-extension/Heter_paper.tex b/mpi-energy2-extension/Heter_paper.tex
index 928c20b..7c2ce1a 100644
--- a/mpi-energy2-extension/Heter_paper.tex
+++ b/mpi-energy2-extension/Heter_paper.tex
@@ -224,11 +224,9 @@ consumption while minimizing the degradation of the program's performance.
 Section~\ref{sec.optim} details the proposed frequencies selecting algorithm.
 Section~\ref{sec.expe} presents the results of applying the algorithm on the 
 NAS parallel benchmarks and executing them on the grid'5000 testbed. 
-%It shows the results of running different scenarios using multi-cores and one core per node and comparing them. 
-It also evaluates the algorithm over three different power scenarios. Moreover, it shows the
+It also evaluates the algorithm over multi-cores per node architectures and over three different power scenarios. Moreover, it shows the
 comparison results between the proposed method and an existing method.  Finally,
 in Section~\ref{sec.concl} the paper ends with a summary and some future works.
-
 \section{Related works}
 \label{sec.relwork}
 
@@ -684,8 +682,7 @@ in~\cite{Zhuo_Energy.efficient.Dynamic.Task.Scheduling,Rauber_Analytical.Modelin
       \State Computations section.
       \State Communications section.
       \If {$(k=1)$}
-        \State Gather all times of computation and\newline\hspace*{3em}%
-               communication from each node.
+        \State Gather all times of computation and communication from each node.
         \State Call Algorithm \ref{HSA}.
         \State Compute the new frequencies from the\newline\hspace*{3em}%
                returned optimal scaling factors.
@@ -861,20 +858,20 @@ The benchmarks have seven different classes, S, W, A, B, C, D and E, that repres
     Name        & model       & Freq. & Freq. & Freq. & per CPU         & of one core     \\
                 &             & GHz   & GHz   & GHz   &                 &           \\
     \hline
-    Taurus      & Intel       & 2.3  & 1.2  & 0.1     & 6               & \np[W]{35} \\
-                & Xeon        &       &       &       &                 &            \\
+                & Intel       & 2.3  & 1.2  & 0.1     & 6               & \np[W]{35} \\
+    Taurus      & Xeon        &       &       &       &                 &            \\
                 & E5-2630     &       &       &       &                 &            \\         
     \hline
-    Graphene    & Intel       & 2.53  & 1.2   & 0.133 & 4               & \np[W]{23} \\
-                & Xeon        &       &       &       &                 &            \\
+                & Intel       & 2.53  & 1.2   & 0.133 & 4               & \np[W]{23} \\
+    Graphene    & Xeon        &       &       &       &                 &            \\
                 & X3440       &       &       &       &                 &            \\    
     \hline
-    Griffon     & Intel       & 2.5   & 2     & 0.5   & 4               & \np[W]{46} \\
-                & Xeon        &       &       &       &                 &            \\
+                & Intel       & 2.5   & 2     & 0.5   & 4               & \np[W]{46} \\
+    Griffon     & Xeon        &       &       &       &                 &            \\
                 & L5420       &       &       &       &                 &            \\  
     \hline
-    Graphite    & Intel       & 2     & 1.2   & 0.1   & 8               & \np[W]{35} \\
-                & Xeon        &       &       &       &                 &            \\
+                & Intel       & 2     & 1.2   & 0.1   & 8               & \np[W]{35} \\
+     Graphite   & Xeon        &       &       &       &                 &            \\
                 & E5-2650     &       &       &       &                 &            \\  
     \hline
   \end{tabular}
@@ -980,9 +977,9 @@ energy saving percentage in one site scenario when executed over 16 nodes compar
   \centering
   \subfloat[The energy consumption by the nodes wile executing the NAS benchmarks over different scenarios    
            ]{%
-    \includegraphics[width=.4\textwidth]{fig/eng_con_scenarios.eps}\label{fig:eng_sen}} \hspace{1cm}%
+    \includegraphics[width=.48\textwidth]{fig/eng_con_scenarios.eps}\label{fig:eng_sen}} \hspace{0.4cm}%
   \subfloat[The execution times of the NAS benchmarks over different scenarios]{%
-    \includegraphics[width=.4\textwidth]{fig/time_scenarios.eps}\label{fig:time_sen}}
+    \includegraphics[width=.48\textwidth]{fig/time_scenarios.eps}\label{fig:time_sen}}
   \label{fig:exp-time-energy}
   \caption{The  energy consumption and execution time of NAS  Benchmarks over different scenarios}
 \end{figure}
@@ -1006,12 +1003,12 @@ The best energy saving percentage was obtained in the one site scenario with 16
 \begin{figure}
   \centering
   \subfloat[The energy reduction while executing the NAS benchmarks over different scenarios ]{%
-    \includegraphics[width=.4\textwidth]{fig/eng_s.eps}\label{fig:eng_s}} \hspace{2cm}%
+    \includegraphics[width=.48\textwidth]{fig/eng_s.eps}\label{fig:eng_s}} \hspace{0.4cm}%
   \subfloat[The performance degradation of the NAS benchmarks over different scenarios]{%
-    \includegraphics[width=.4\textwidth]{fig/per_d.eps}\label{fig:per_d}}\hspace{2cm}%
+    \includegraphics[width=.48\textwidth]{fig/per_d.eps}\label{fig:per_d}}\hspace{0.4cm}%
     \subfloat[The tradeoff distance between the energy reduction and the performance of the NAS benchmarks  
       over different scenarios]{%
-    \includegraphics[width=.4\textwidth]{fig/dist.eps}\label{fig:dist}}
+    \includegraphics[width=.48\textwidth]{fig/dist.eps}\label{fig:dist}}
   \label{fig:exp-res}
   \caption{The experimental results of different scenarios}
 \end{figure}
@@ -1077,9 +1074,9 @@ Scenario name                          & Cluster name & \begin{tabular}[c]{@{}c@
 \begin{figure}
   \centering
   \subfloat[Comparing the  execution times of running NAS benchmarks over one core and multicores scenarios]{%
-    \includegraphics[width=.4\textwidth]{fig/time.eps}\label{fig:time-mc}} \hspace{1cm}%
+    \includegraphics[width=.48\textwidth]{fig/time.eps}\label{fig:time-mc}} \hspace{0.4cm}%
   \subfloat[Comparing the  energy consumptions of running NAS benchmarks over one core and multi-cores scenarios]{%
-    \includegraphics[width=.4\textwidth]{fig/eng_con.eps}\label{fig:eng-cons-mc}}
+    \includegraphics[width=.48\textwidth]{fig/eng_con.eps}\label{fig:eng-cons-mc}}
     \label{fig:eng-cons}
   \caption{The energy consumptions and execution times of NAS benchmarks over one core and multi-cores per node architectures}
 \end{figure}
@@ -1117,12 +1114,12 @@ in the figure \ref{fig:dist-mc}. These  tradeoff distance between energy consump
 \begin{figure}
   \centering
     \subfloat[The energy saving of running NAS benchmarks over one core and multicores scenarios]{%
-    \includegraphics[width=.4\textwidth]{fig/eng_s_mc.eps}\label{fig:eng-s-mc}} \hspace{2cm}%
+    \includegraphics[width=.48\textwidth]{fig/eng_s_mc.eps}\label{fig:eng-s-mc}} \hspace{0.4cm}%
     \subfloat[The performance degradation of running NAS benchmarks over one core and multicores scenarios
       ]{%
-    \includegraphics[width=.4\textwidth]{fig/per_d_mc.eps}\label{fig:per-d-mc}}\hspace{2cm}%
+    \includegraphics[width=.48\textwidth]{fig/per_d_mc.eps}\label{fig:per-d-mc}}\hspace{0.4cm}%
     \subfloat[The tradeoff distance of running NAS benchmarks over one core and multicores scenarios]{%
-    \includegraphics[width=.4\textwidth]{fig/dist_mc.eps}\label{fig:dist-mc}}
+    \includegraphics[width=.48\textwidth]{fig/dist_mc.eps}\label{fig:dist-mc}}
   \label{fig:exp-res}
   \caption{The experimental results of one core and multi-cores scenarios}
 \end{figure}
@@ -1143,12 +1140,12 @@ In these experiments, the class D of the NAS parallel benchmarks are executed ov
 \begin{figure}
   \centering
   \subfloat[The energy saving percentages for the nodes executing the NAS benchmarks over the three power scenarios]{%
-    \includegraphics[width=.4\textwidth]{fig/eng_pow.eps}\label{fig:eng-pow}} \hspace{2cm}%
+    \includegraphics[width=.48\textwidth]{fig/eng_pow.eps}\label{fig:eng-pow}} \hspace{0.4cm}%
   \subfloat[The performance degradation percentages for the NAS benchmarks over the three power scenarios]{%
-    \includegraphics[width=.4\textwidth]{fig/per_pow.eps}\label{fig:per-pow}}\hspace{2cm}%
+    \includegraphics[width=.48\textwidth]{fig/per_pow.eps}\label{fig:per-pow}}\hspace{0.4cm}%
     \subfloat[The tradeoff distance between the energy reduction and the performance of the NAS benchmarks over the three power scenarios]{%
       
-    \includegraphics[width=.4\textwidth]{fig/dist_pow.eps}\label{fig:dist-pow}}
+    \includegraphics[width=.48\textwidth]{fig/dist_pow.eps}\label{fig:dist-pow}}
   \label{fig:exp-pow}
   \caption{The experimental results of different static power scenarios}
 \end{figure}
@@ -1208,11 +1205,11 @@ presented in the figures \ref{fig:edp-eng}, \ref{fig:edp-perf} and \ref{fig:edp-
 \begin{figure}
   \centering
   \subfloat[The energy reduction induced by the Maxdist method and the EDP method]{%
-    \includegraphics[width=.4\textwidth]{fig/edp_eng}\label{fig:edp-eng}} \hspace{2cm}%
+    \includegraphics[width=.48\textwidth]{fig/edp_eng}\label{fig:edp-eng}} \hspace{0.4cm}%
     \subfloat[The performance degradation induced by  the Maxdist method and the EDP method]{%
-    \includegraphics[width=.4\textwidth]{fig/edp_per}\label{fig:edp-perf}}\hspace{2cm}%
+    \includegraphics[width=.48\textwidth]{fig/edp_per}\label{fig:edp-perf}}\hspace{0.4cm}%
     \subfloat[The tradeoff distance between the energy consumption reduction and the performance for the Maxdist method and the  EDP method]{%
-    \includegraphics[width=.4\textwidth]{fig/edp_dist}\label{fig:edp-dist}}
+    \includegraphics[width=.48\textwidth]{fig/edp_dist}\label{fig:edp-dist}}
   \label{fig:edp-comparison}
   \caption{The comparison results}
 \end{figure}
@@ -1242,7 +1239,7 @@ To evaluate the proposed method on a real heterogeneous grid platform, it was ap
  NAS parallel benchmarks   and the  class D instance was executed over the  grid'5000 testbed platform. 
  The experimental results showed that the algorithm reduces  on average 30\% of the energy consumption
 for all the NAS benchmarks   while  only degrading by 3.2\% on average  the performance. 
-The Maxdist algorithm was also evaluated in different scenarios that vary in the distribution of the computing nodes between different clusters' sites or between using one core and multi-cores per node or in the values of the consumed static power. The algorithm selects different vector of frequencies according to the 
+The Maxdist algorithm was also evaluated in different scenarios that vary in the distribution of the computing nodes between different clusters' sites or  use multi-cores per node architecture or consume different static power values. The algorithm selects different vector of frequencies according to the 
 computations and communication times ratios, and  the values of the static and measured dynamic powers of the CPUs. 
 Finally, the proposed algorithm was compared to another method that uses
 the well known energy and delay product as an objective function. The comparison results showed 
