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[book_gpu.git] / BookGPU / Chapters / chapter4 / ch4.tex

diff --git a/BookGPU/Chapters/chapter4/ch4.tex b/BookGPU/Chapters/chapter4/ch4.tex
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--- a/BookGPU/Chapters/chapter4/ch4.tex
+++ b/BookGPU/Chapters/chapter4/ch4.tex
@@ -1,4 +1,7 @@
-\chapterauthor{Gilles Perrot}{FEMTO-ST Institute}
+\chapterauthor{Gilles Perrot}{Femto-ST Institute, University of Franche-Comte, France}
+
+\chapter{Implementing an efficient convolution operation on GPU}
+

 
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@@ -29,10 +32,10 @@
 %%   }
 
 
 %%   }
 
 

-\chapter{Implementing an efficient convolution \index{Convolution} operation on GPU}
+

 \section{Overview}
 In this chapter, after dealing with GPU median filter implementations,
 \section{Overview}
 In this chapter, after dealing with GPU median filter implementations,

-we propose to explore how convolutions can be implemented on modern
+we propose to explore how convolutions\index{Convolution}  can be implemented on modern

 GPUs. Widely used in digital image processing filters, the \emph{convolution
 operation} basically consists in taking the sum of products of elements
 from two 2-D functions, letting one of the two functions move over
 GPUs. Widely used in digital image processing filters, the \emph{convolution
 operation} basically consists in taking the sum of products of elements
 from two 2-D functions, letting one of the two functions move over