From: afanfakh <afanfakh@fanfakh.afanfakh>
Date: Tue, 20 Oct 2015 10:09:47 +0000 (+0200)
Subject: adding fig
X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/mpi-energy2.git/commitdiff_plain/c74b7c683485074df4b36469667a8d8c65a18861?ds=inline

adding fig
---

diff --git a/mpi-energy2-extension/Heter_paper.tex b/mpi-energy2-extension/Heter_paper.tex
index 1fe16cf..d157b79 100644
--- a/mpi-energy2-extension/Heter_paper.tex
+++ b/mpi-energy2-extension/Heter_paper.tex
@@ -85,6 +85,35 @@
 
 \maketitle
 
+
+\begin{abstract}
+
+  In recent years, green computing topic  has being became an important topic in 
+  the domain of the research. The increase in computing power of the computing 
+  platforms is increased the energy consumption and the carbon dioxide emissions.
+  Many techniques have being used to minimize the cost of the energy consumption 
+  and reduce environmental pollution. Dynamic voltage and frequency scaling (DVFS) 
+  is one of these techniques. It used to reduce the power consumption of the CPU 
+  while computing by lowering its frequency. Moreover, lowering the frequency of 
+  a CPU may increase the execution time of an application running on that 
+  processor. Therefore, the frequency that gives the best trade-off between 
+  the energy consumption and the performance of an application must be selected. 
+
+  In this paper, a new online frequency selecting algorithm for heterogeneous
+  grid (heterogeneous CPUs) is presented.  It selects the frequencies and tries to give the best
+  trade-off between energy saving and performance degradation, for each node
+  computing the message passing iterative application. The algorithm has a small
+  overhead and works without training or profiling. It uses a new energy model
+  for message passing iterative applications running on a heterogeneous
+  grid. The proposed algorithm is evaluated on real testbed, grid'5000 platform, while
+  running the NAS parallel benchmarks.  The experiments show that it reduces the
+  energy consumption on average up to \np[\%]{30} while declines the performance
+  on average by \np[\%]{3} only for the same instance. Finally, the algorithm is 
+  compared to an existing method, the comparison results show that it outperforms the
+  latter in term of energy and performance trade-off.
+\end{abstract}
+
+
 \section{Introduction}
 \label{sec.intro}
 \textcolor{blue}{