MAJ de quelque commentaire pour les figures....

[kahina_paper1.git] / paper.tex

diff --git a/paper.tex b/paper.tex
index 91bdab7af02177a97b9e40a6974566ae2ed4f0e8..38d91d8e0fafd437c71caf98b290767bb39229bb 100644 (file)
--- a/paper.tex
+++ b/paper.tex
@@ -642,7 +642,7 @@ We report the execution times of the Ehrlisch-Aberth method implemented on one c
 
 
 \subsubsection{Influence of the number of threads on the execution times of different polynomials (sparse and full)}
 
 
 \subsubsection{Influence of the number of threads on the execution times of different polynomials (sparse and full)}

-It is also interesting to see the influence of the number of threads per block on the execution time. For that, we notice that the maximum number of threads per block for the Nvidia Tesla K40c GPU is 1024, so we varied the number of threads per block from 8 to 1024.we took into account the execution time for both sparse and full polynomials of size 50000 and 500000 degrees.
+It is also interesting to see the influence of the number of threads per block on the execution time. For that, we notice that the maximum number of threads per block for the Nvidia Tesla K40c GPU is 1024, so we varied the number of threads per block from 8 to 1024. We took into account the execution time for both sparse and full polynomials of size 50000 and 500000 degrees.

 
 \begin{figure}[H]
 \centering
 
 \begin{figure}[H]
 \centering


@@ -651,7 +651,7 @@ It is also interesting to see the influence of the number of threads per block o
 \label{fig:01}
 \end{figure}
 
 \label{fig:01}
 \end{figure}
 

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

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