Ajout du code Kernel testConvergence

[kahina_paper1.git] / paper.tex

diff --git a/paper.tex b/paper.tex
index 44f01e2b82c98e41186e7f2e38055ab82dbc099d..93e111a25b99fa7ed144d0eda0446aaa3d4ae8f9 100644 (file)
--- a/paper.tex
+++ b/paper.tex
@@ -9,6 +9,15 @@
 \usepackage[ruled,vlined]{algorithm2e}
 %\usepackage[french,boxed,linesnumbered]{algorithm2e}
 \usepackage{array,multirow,makecell}
+
+\newcommand{\RC}[2][inline]{%
+  \todo[color=blue!10,#1]{\sffamily\textbf{RC:} #2}\xspace}
+\newcommand{\KG}[2][inline]{%
+  \todo[color=green!10,#1]{\sffamily\textbf{KG:} #2}\xspace}
+\newcommand{\AS}[2][inline]{%
+  \todo[color=orange!10,#1]{\sffamily\textbf{AS:} #2}\xspace}
+
+
 \setcellgapes{1pt}
 \makegapedcells
 \newcolumntype{R}[1]{>{\raggedleft\arraybackslash }b{#1}}
@@ -16,6 +25,8 @@
 \newcolumntype{C}[1]{>{\centering\arraybackslash }b{#1}}
 \modulolinenumbers[5]
 
+
+
 \journal{Journal of \LaTeX\ Templates}
 
 %%%%%%%%%%%%%%%%%%%%%%%
@@ -88,7 +99,7 @@ the results of a parallel implementation of the Ehrlich-Aberth
 algorithm for the root finding problem for high degree polynomials on
 GPU architectures. The main result of this
 work is to be able to solve high degree polynomials (up
-to 1,000,000) very efficiently. We also compare the results with a
+to 1,000,000)  efficiently. We also compare the results with a
 sequential implementation and the Durand-Kerner method on full and
 sparse polynomials.
 \end{abstract}