\subsection{The experimental results of the scaling algorithm}
\label{sec.res}
-In this section, the scaling factor selection algorithm \ref{HSA}, is applied
-to NAS parallel benchmarks. Seven benchmarks, CG, MG, EP, LU, BT, SP and FT, of the class D
-are executed over grid'5000 computing clusters. As mentioned previously, the experiments
-of this paper obtained from a collection of many clusters distributed in two sites, Lyon and Nancy sites,
-of grid'5000. Four different clusters are selected from these two sites to generate two
-different scenarios. Each of these two scenarios used three clusters. The first scenario,
-is composed from three clusters that located in two sites, Lyon and Nancy sites. One of these three
-clusters is from Lyon site, Taurus cluster and the other two clusters are form Nancy site,
-Graphene and Griffon clusters. The second scenario, is composed from three clusters that are
-located in one site, Nancy site. These cluster are Graphite, Graphene and griffon. The main reason
-behind using these two scenarios is because the first one is executing the NAS parllel benchmarks over
-two sites that are connected via long distance network, then the computations to communications ratio
-is very low due to the increase in communication times, while in the second scenario, all of the three clusters are
-located in one site and they are connected via high speed local area networks, where the computations
-to communications ratio is higher. Therefore, it is very interested to know the performance behaviour
-and the energy consumption of NAS parallel benchmarks using the proposed method, when they run
-over these two different platform scenarios. Moreover, The NAS parallel benchmarks are executed over
+In this section, the results of the the application of the scaling factors selection algorithm \ref{HSA}
+to the NAS parallel benchmarks are presented.
+
+As mentioned previously, the experiments
+were conducted over two sites of grid'5000, Lyon and Nancy sites.
+Two scenarios were considered while selecting the clusters from these two sites :
+\begin{itemize}
+\item In the first scenario, nodes from two sites and three heterogeneous clusters were selected. The two sites are connected
+are connected via a long distance network.
+\item In the second scenario nodes from three clusters that are
+located in one site, Nancy site.
+\end{itemize}
+
+The main reason
+behind using these two scenarios is to evaluate the influence of long distance communications (higher latency) on the performance of the
+scaling factors selection algorithm. Indeed, in the first scenario the computations to communications ratio
+is very low due to the higher communication times which reduces the effect of DVFS operations.
+
+The NAS parallel benchmarks are executed over
16 and 32 nodes for each scenario. The number of participating computing nodes form each cluster
-are different, this depends on the available number of nodes in each cluster.
-Table \ref{tab:sc} shows the details of these two scenarios and the number of nodes
-used from each cluster.
+are different because all the selected clusters do not have the same available number of nodes and all benchmarks do not require the same number of computing nodes.
+Table \ref{tab:sc} shows the number of nodes used from each cluster for each scenario.
\begin{table}[h]
\caption{The different clusters scenarios}
\centering
-\begin{tabular}{|*{3}{c|}}
+\begin{tabular}{|*{4}{c|}}
\hline
-\multirow{2}{*}{Scenario name} & \multicolumn{2}{c|} {The participating clusters} \\ \cline{2-3}
- & Cluster name & No. of nodes of each cluster \\
+\multirow{2}{*}{Scenario name} & \multicolumn{2}{c|} {The participating clusters} \\ \cline{2-4}
+ & Cluster & Site & No. of nodes \\
\hline
-\multirow{3}{*}{Two sites / 16 nodes} & Taurus & 5 \\ \cline{2-3}
- & Graphene & 5 \\ \cline{2-3}
- & Griffon & 6 \\
+\multirow{3}{*}{Two sites / 16 nodes} & Taurus & Lyon & 5 \\ \cline{2-4}
+ & Graphene & Nancy & 5 \\ \cline{2-4}
+ & Griffon & Nancy & 6 \\
\hline
-\multirow{3}{*}{Tow sites / 32 nodes} & Taurus & 10 \\ \cline{2-3}
- & Graphene & 10 \\ \cline{2-3}
- & Griffon & 12 \\
+\multirow{3}{*}{Tow sites / 32 nodes} & Taurus & Lyon & 10 \\ \cline{2-4}
+ & Graphene & Nancy & 10 \\ \cline{2-4}
+ & Griffon &Nancy & 12 \\
\hline
-\multirow{3}{*}{One site / 16 nodes} & Graphite & 4 \\ \cline{2-3}
- & Graphene & 6 \\ \cline{2-3}
- & Griffon & 6 \\
+\multirow{3}{*}{One site / 16 nodes} & Graphite & Nancy & 4 \\ \cline{2-4}
+ & Graphene & Nancy & 6 \\ \cline{2-4}
+ & Griffon & Nancy & 6 \\
\hline
-\multirow{3}{*}{One site / 32 nodes} & Graphite & 4 \\ \cline{2-3}
- & Graphene & 12 \\ \cline{2-3}
- & Griffon & 12 \\
+\multirow{3}{*}{One site / 32 nodes} & Graphite & Nancy & 4 \\ \cline{2-4}
+ & Graphene & Nancy & 12 \\ \cline{2-4}
+ & Griffon & Nancy & 12 \\
\hline
\end{tabular}
\label{tab:sc}
\end{figure}
The NAS parallel benchmarks are executed over these two platform
-scenarios with different number of nodes, as in Table \ref{tab:sc}.
-The overall energy consumption of all benchmark, class D, with
-applying the proposed frequency selection algorithm is measured
+ with different number of nodes, as in Table \ref{tab:sc}.
+The overall energy consumption of all the benchmarks solving the class D instance and
+using the proposed frequency selection algorithm is measured
using the equation of the reduced energy consumption, equation
(\ref{eq:energy}). This model uses the measured dynamic and static
-power values that showed in Table \ref{table:grid5000}. The execution
-time is measured for all benchmarks over these different scenarios.
-The energy consumptions and the execution times for all benchmarks are
-demonstrated in the plots \ref{fig:eng_sen} and \ref{fig:time_sen} respectively.
-In general, the energy consumptions of NAS benchmarks over one site scenario
-for 16 and 32 nodes are less than those executed over the two sites
-scenarios. This because in the two sites scenario the communication times
-are higher, due to long distance communications between the two distributed sites.
-This leading to more static energy consumption which is linearly related to the
-increased in the communication time. The execution times of these benchmarks
-over one sites for 16 and 32 nodes are less comparing to the two sites
-scenario according to the increase in communications times.
+power values showed in Table \ref{table:grid5000}. The execution
+time is measured for all the benchmarks over these different scenarios.
+
+The energy consumptions and the execution times for all the benchmarks are
+presented in the plots \ref{fig:eng_sen} and \ref{fig:time_sen} respectively.
+
+In general, the energy consumed while executing the NAS benchmarks over one site scenario
+for 16 and 32 nodes is lower than the energy consumed while executing over the two sites.
+The long distance communications between the two distributed sites increases the idle time which leads to more static energy consumption.
+ The execution times of these benchmarks
+over one site with 16 and 32 nodes are also lower when compared to those of the two sites
+scenario.
+
+
The EP and MG benchmarks, where there are no or small communications, showed
that their execution times and the energy consumptions are not effected
