X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/book_gpu.git/blobdiff_plain/fa1939d2294b408e8a62f2d91149f369f8710113..453cfeb12ac41d9063d5fb8f41ee725905b3adec:/BookGPU/Chapters/chapter1/ch1.tex?ds=sidebyside

diff --git a/BookGPU/Chapters/chapter1/ch1.tex b/BookGPU/Chapters/chapter1/ch1.tex
index 17a7e47..200efb1 100755
--- a/BookGPU/Chapters/chapter1/ch1.tex
+++ b/BookGPU/Chapters/chapter1/ch1.tex
@@ -1,7 +1,7 @@
 \chapterauthor{Raphaël Couturier}{Femto-ST Institute, University of Franche-Comte, France}
 
 
-\chapter{Presentation of the GPU architecture and of the Cuda environment}
+\chapter{Presentation of the GPU architecture and of the CUDA environment}
 \label{chapter1}
 
 \section{Introduction}\label{ch1:intro}
@@ -9,7 +9,7 @@
 This chapter introduces the Graphics  Processing Unit (GPU) architecture and all
 the concepts needed to understand how GPUs  work and can be used to speed up the
 execution of some algorithms. First of all this chapter gives a brief history of
-the development  of Graphics  card until they  have been  used in order  to make
+the development  of the graphics  cards until they  have been  used in order  to make
 general   purpose   computation.    Then   the   architecture  of   a   GPU   is
 illustrated.  There  are  many  fundamental  differences between  a  GPU  and  a
 tradition  processor. In  order  to benefit  from the  power  of a  GPU, a  Cuda
@@ -18,7 +18,7 @@ Cuda model to be efficient and scalable when some constraints are addressed.
 
 
 
-\section{Brief history of Video Card}
+\section{Brief history of video card}
 
 Video  cards or Graphics  cards have  been introduced  in personal  computers to
 produce  high quality graphics  faster than  classical Central  Processing Units
@@ -174,7 +174,7 @@ Task parallelism is the common parallelism  achieved out on clusters and grids a
 high performance  architectures where different tasks are  executed by different
 computing units.
 
-\section{Cuda Multithreading}
+\section{CUDA multithreading}
 
 The data parallelism  of Cuda is more precisely based  on the Single Instruction
 Multiple Thread (SIMT) model. This is due to the fact that a programmer accesses