X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/mpi-energy2.git/blobdiff_plain/c21fdc56ee3f50369bfd1f4fcb5caa5c4255a570..e2d0acd1461bf4e64de95e87f02267cc513c1094:/Heter_paper.tex?ds=inline

diff --git a/Heter_paper.tex b/Heter_paper.tex
index 4689caf..8b0f807 100644
--- a/Heter_paper.tex
+++ b/Heter_paper.tex
@@ -785,13 +785,13 @@ nodes were connected via an Ethernet network with 1 Gbit/s bandwidth.
 
 
 The proposed algorithm was applied to the seven parallel NAS benchmarks (EP, CG,
-MG, FT, BT, LU and SP) and  the benchmarks were executed with the three classes:
+MG, FT, BT, LU and SP) and the benchmarks were executed with the three classes:
 A, B and C. However, due to the lack of space in this paper, only the results of
-the  biggest class,  C, are  presented while  being run  on different  number of
-nodes,  ranging from 4  to 128  or 144  nodes depending  on the  benchmark being
-executed. Indeed, the benchmarks CG, MG, LU, EP and FT had to be executed on $1,
-2, 4, 8, 16, 32, 64, 128$ nodes.   The other benchmarks such as BT and SP had to
-be executed on $1, 4, 9, 16, 36, 64, 144$ nodes.
+the biggest class, C, are presented while being run on different number of
+nodes, ranging from 4 to 128 or 144 nodes depending on the benchmark being
+executed. Indeed, the benchmarks CG, MG, LU, EP and FT had to be executed on 1,
+2, 4, 8, 16, 32, 64, or 128 nodes.  The other benchmarks such as BT and SP had
+to be executed on 1, 4, 9, 16, 36, 64, or 144 nodes.
 
  
  
@@ -981,7 +981,7 @@ significantly reduces the energy consumption (up to \np[\%]{35}) and tries to
 limit the performance degradation.  They also show that the energy saving
 percentage decreases when the number of computing nodes increases.  This
 reduction is due to the increase of the communication times compared to the
-execution times when the benchmarks are run over a high number of nodes.
+execution times when the benchmarks are run over a higher number of nodes.
 Indeed, the benchmarks with the same class, C, are executed on different numbers
 of nodes, so the computation required for each iteration is divided by the
 number of computing nodes.  On the other hand, more communications are required