MAJ de la figure 3

[kahina_paper1.git] / paper.tex

diff --git a/paper.tex b/paper.tex
index 7ef63458a6462d561214345c3ed15b6de3810c3a..34b803c7d5986d54a68bf46555ee9c48555e20e1 100644 (file)
--- a/paper.tex
+++ b/paper.tex
@@ -365,6 +365,7 @@ Q(z^{k}_{i})=\exp\left( \ln (p(z^{k}_{i}))-\ln(p'(z^{k}_{i}))+\ln \left(
 \end{equation}
 
 This solution is applied when the root except the circle unit, represented by the radius $R$ evaluated in C language as:
 \end{equation}
 
 This solution is applied when the root except the circle unit, represented by the radius $R$ evaluated in C language as:

+

 \begin{verbatim}
 R = exp(log(DBL_MAX)/(2*n) );
 \end{verbatim} 
 \begin{verbatim}
 R = exp(log(DBL_MAX)/(2*n) );
 \end{verbatim} 


@@ -731,20 +732,17 @@ For that, we notice that the maximum number of threads per block for the Nvidia
 
 The figure 2 show that, the best execution time for both sparse and full polynomial are given when the threads number varies between 64 and 256 threads per bloc. We notice that with small polynomials the best number of threads per block is 64, Whereas, the large polynomials the best number of threads per block is 256. However,In the following experiments we specify that the number of thread by block is 256.
 
 
 The figure 2 show that, the best execution time for both sparse and full polynomial are given when the threads number varies between 64 and 256 threads per bloc. We notice that with small polynomials the best number of threads per block is 64, Whereas, the large polynomials the best number of threads per block is 256. However,In the following experiments we specify that the number of thread by block is 256.
 

-\subsection{The impact of exp-log solution to compute very high degrees of  polynomial}
+\subsection{The impact of exp.log solution to compute very high degrees of  polynomial}

 
 

-<<<<<<< HEAD

 In this experiment we report the performance of exp-log solution described in Section~\ref{sec2} to compute very high degrees polynomials.   
 In this experiment we report the performance of exp-log solution described in Section~\ref{sec2} to compute very high degrees polynomials.   

-=======
-In this experiment we report the performance of log.exp solution describe in ~\ref{sec2} to compute very high degrees polynomials.   
->>>>>>> 7f2978c0d220516decb65faf2b8ba2da34df8db2

 \begin{figure}[htbp]
 \centering
   \includegraphics[width=0.8\textwidth]{figures/sparse_full_explog}
 \begin{figure}[htbp]
 \centering
   \includegraphics[width=0.8\textwidth]{figures/sparse_full_explog}

-\caption{The impact of exp-log solution to compute very high degrees of  polynomial.}
+\caption{The impact of exp.log solution to compute very high degrees of  polynomial.}

 \label{fig:03}
 \end{figure}
 
 \label{fig:03}
 \end{figure}
 

+

 Figure~\ref{fig:03} shows a comparison between the execution time of
 the Ehrlich-Aberth algorithm using the exp.log solution and the
 execution time of the Ehrlich-Aberth algorithm without this solution,
 Figure~\ref{fig:03} shows a comparison between the execution time of
 the Ehrlich-Aberth algorithm using the exp.log solution and the
 execution time of the Ehrlich-Aberth algorithm without this solution,


@@ -761,6 +759,7 @@ high degree polynomials.
 
 
 
 
 
 

+

 \subsection{Comparison of the Durand-Kerner and the Ehrlich-Aberth methods}
 
 In this part, we  compare the Durand-Kerner and the Ehrlich-Aberth
 \subsection{Comparison of the Durand-Kerner and the Ehrlich-Aberth methods}
 
 In this part, we  compare the Durand-Kerner and the Ehrlich-Aberth