X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/kahina_paper1.git/blobdiff_plain/342f7f0e63333d70a4bc6987bc7df003ac491488..065c8445483c2244976fa7af7a1dfc81f6e0096e:/paper.tex

diff --git a/paper.tex b/paper.tex
index df35ecb..73a2b47 100644
--- a/paper.tex
+++ b/paper.tex
@@ -1,9 +1,10 @@
 \documentclass[review]{elsarticle}
 
-\usepackage{lineno,hyperref}
-%%\usepackage[utf8]{inputenc}
+\usepackage{lineno,hyperref}  
+\usepackage[utf8]{inputenc}
 %%\usepackage[T1]{fontenc}
 %%\usepackage[french]{babel}
+
 \usepackage{amsmath,amsfonts,amssymb}
 \usepackage[ruled,vlined]{algorithm2e}
 \usepackage{array,multirow,makecell}
@@ -55,9 +56,9 @@
 \title{A parallel  root finding polynomial on GPU}
 
 %% Group authors per affiliation:
-\author{Elsevier\fnref{myfootnote}}
-\address{Radarweg 29, Amsterdam}
-\fntext[myfootnote]{Since 1880.}
+%\author{Elsevier\fnref{myfootnote}}
+%\address{Radarweg 29, Amsterdam}
+%\fntext[myfootnote]{Since 1880.}
 
 %% or include affiliations in footnotes:
 \author[mymainaddress]{Ghidouche Kahina\corref{mycorrespondingauthor}}
@@ -65,7 +66,7 @@
 \cortext[mycorrespondingauthor]{Corresponding author}
 \ead{kahina.ghidouche@gmail.com}
 
-\author[mysecondaryaddress]{Couturier Raphael\corref{mycorrespondingauthor}}
+\author[mysecondaryaddress]{Couturier Raphaël\corref{mycorrespondingauthor}}
 %%\cortext[mycorrespondingauthor]{Corresponding author}
 \ead{raphael.couturier@univ-fcomte.fr}
 
@@ -73,8 +74,10 @@
 %%\cortext[mycorrespondingauthor]{Corresponding author}
 \ead{ar.sider@univ-bejaia.dz}
 
-\address[mymainaddress]{Department of informatics,University of Bejaia,Algeria}
-\address[mysecondaryaddress]{FEMTO-ST Institute, University of Franche-Compté }
+\address[mymainaddress]{Department of informatics, University of
+  Béjaia, Algeria}
+\address[mysecondaryaddress]{FEMTO-ST Institute, University of
+  Bourgogne Franche-Comte }
 
 \begin{abstract}
 in this article we present a parallel implementation
@@ -451,7 +454,7 @@ The means steps of Aberth method can expressed as an algorithm
 like:
   
 \begin{algorithm}[H]
-\LinesNumbered
+%\LinesNumbered
 \caption{Algorithm to find root polynomial with Aberth method}
 
 \KwIn{$Z^{0}$(Initial root's vector),$\varepsilon$ (error
@@ -529,7 +532,7 @@ In theory, the $Total\_time_{exe}$ on GPU is speed up nbr\_thread times as a $To
 In CUDA platform, All the instruction of the loop \verb=for= are executed by the GPU as a kernel form. A kernel is a procedure written in CUDA and defined by a heading \verb=__global__=, which means that it is to be executed by the GPU. The following algorithm see the Aberth algorithm on GPU:
 
 \begin{algorithm}[H]
-\LinesNumbered
+%\LinesNumbered
 \caption{Algorithm to find root polynomial with Aberth method}
 
 \KwIn{$Z^{0}$(Initial root's vector),$\varepsilon$ (error
@@ -557,7 +560,7 @@ After the initialization step, all data of the root finding problem to be solved
 The second kernel executes the iterative function and update Z(k),as formula (), we notice that the kernel update are called in two forms,  separated with  the value of \emph{R} which determines the radius beyond which we apply the logarithm formula like this: 
 
 \begin{algorithm}[H]
-\LinesNumbered
+%\LinesNumbered
 \caption{A global Algorithm for the iterative function}
 
 \eIf{$(\left|Z^{(k)}\right|<= R)$}{
@@ -672,4 +675,4 @@ We initially carried out the convergence of Aberth algorithm with various sizes
 
 \bibliography{mybibfile}
 
-\end{document}
\ No newline at end of file
+\end{document}