X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/book_gpu.git/blobdiff_plain/4eb0d6980c190aa2e92700dd01c5f685405590bd..e4346947aa62df9cab78e792050767d42c5f5ab3:/BookGPU/Chapters/chapter2/ch2.tex?ds=sidebyside

diff --git a/BookGPU/Chapters/chapter2/ch2.tex b/BookGPU/Chapters/chapter2/ch2.tex
index 501e34e..c33ac50 100755
--- a/BookGPU/Chapters/chapter2/ch2.tex
+++ b/BookGPU/Chapters/chapter2/ch2.tex
@@ -137,6 +137,8 @@ consider  we  have  a  squared  matrix  of size  \texttt{size}.  So  with  a  1D
 array, \texttt{A[i*size+j]} allows  us to access to the  element of the $i^{th}$
 row and of the $j^{th}$ column.
 
+In sequential the matrix multiplication is performed using three loops. Supposing that $A$, $B$ represent two square matrices, the result of the multiplication of $A \times B$ is 
+
 On C2070M Tesla card, this code take 37.68ms to perform the multiplication. On a
 Intel Xeon E31245 at 3.30GHz, it takes 2465ms without any parallelization (using
 only one  core). Consequently the  speed up between  the CPU and GPU  version is