X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/book_gpu.git/blobdiff_plain/17bff40b83bcdcc39769f9e59c70ffae1c525b72..57e564506a8117605eca5b5d80c0f492e6121c12:/BookGPU/Chapters/chapter6/PartieSync.tex

diff --git a/BookGPU/Chapters/chapter6/PartieSync.tex b/BookGPU/Chapters/chapter6/PartieSync.tex
index d8d281c..ce21565 100755
--- a/BookGPU/Chapters/chapter6/PartieSync.tex
+++ b/BookGPU/Chapters/chapter6/PartieSync.tex
@@ -97,7 +97,7 @@ parallel programming schemes on a GPU cluster:
 Using CUDA\index{CUDA}, GPU kernel executions are nonblocking, and GPU/CPU data
 transfers\index{CUDA!data transfer}
 are blocking or nonblocking operations. All GPU kernel executions and CPU/GPU
-data transfers are associated to "streams,"\index{CUDA!stream} and all operations on a same stream
+data transfers are associated to ``streams'',\index{CUDA!stream} and all operations on a same stream
 are serialized. When transferring data from the CPU to the GPU, then running GPU
 computations, and finally transferring results from the GPU to the CPU, there is
 a natural synchronization and serialization if these operations are achieved on
@@ -489,7 +489,7 @@ working on  independent subsets of  data.  \Lst{algo:ch6p1overlapstreamsequence}
 is not so generic as \Lst{algo:ch6p1overlapseqsequence}.
 
 
-\subsection{Interleaved communications-transfers-computations\\overlapping}
+\subsection{Interleaved communications-transfers-computations overlapping}
 
 Many algorithms do not support splitting data transfers and kernel calls, and
 cannot exploit CUDA streams, for example, when each GPU thread requires access to