new

[book_gpu.git] / BookGPU / Chapters / chapter1 / ch1.tex

diff --git a/BookGPU/Chapters/chapter1/ch1.tex b/BookGPU/Chapters/chapter1/ch1.tex
index a70f420c51a3cbee1a4e7935b2fb1295ffe73bda..fc891b5f7311338c3bf99c97290f99958366941e 100755 (executable)
--- a/BookGPU/Chapters/chapter1/ch1.tex
+++ b/BookGPU/Chapters/chapter1/ch1.tex
@@ -5,7 +5,7 @@
 \label{chapter1}
 
 \section{Introduction}\label{ch1:intro}
 \label{chapter1}
 
 \section{Introduction}\label{ch1:intro}

-
+``test"  "test" ``test''

 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
 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


@@ -68,7 +68,7 @@ example  we can  cite, FireStream  by ATI  which is  not maintained  anymore and
 has been replaced by  OpenCL, BrookGPU by  Standford University~\cite{ch1:Buck:2004:BGS}.
 Another environment based  on pragma (insertion of pragma  directives inside the
 code to  help the compiler to generate  efficient code) is called  OpenACC.  For a
 has been replaced by  OpenCL, BrookGPU by  Standford University~\cite{ch1:Buck:2004:BGS}.
 Another environment based  on pragma (insertion of pragma  directives inside the
 code to  help the compiler to generate  efficient code) is called  OpenACC.  For a

-comparison with OpenCL, interested readers may refer to~\cite{ch1:CMR:12}.
+comparison with OpenCL, interested readers may refer to~\cite{ch1:Dongarra}.

 
 
 
 
 
 


@@ -113,7 +113,7 @@ Threads are used to  benefit from the large number of cores  of a GPU. These
 threads    are   different    from    traditional   threads    for a   CPU.     In
 Chapter~\ref{chapter2},  some  examples of  GPU  programming  will explain  the
 details of  the GPU  threads. Threads are gathered  into blocks  of 32
 threads    are   different    from    traditional   threads    for a   CPU.     In
 Chapter~\ref{chapter2},  some  examples of  GPU  programming  will explain  the
 details of  the GPU  threads. Threads are gathered  into blocks  of 32

-threads, called warps. These warps  are important when designing an algorithm
+threads, called ``warps''. These warps  are important when designing an algorithm

 for GPU.
 
 
 for GPU.