X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/book_gpu.git/blobdiff_plain/cacf1137755cd5d5eba063f453055e49a25d579f..8fc4c8914177b38f8042870c31065ea619b900ec:/BookGPU/Chapters/chapter15/ch15.tex

diff --git a/BookGPU/Chapters/chapter15/ch15.tex b/BookGPU/Chapters/chapter15/ch15.tex
index 7e25220..2d507e4 100644
--- a/BookGPU/Chapters/chapter15/ch15.tex
+++ b/BookGPU/Chapters/chapter15/ch15.tex
@@ -670,7 +670,7 @@ Fig.~\ref{offdiagonal} for an off-diagonal sector.
   These copies, along with possible scalings or transpositions, are
   implemented as CUDA kernels which can be applied to two
   matrices of any size starting at any offset. 
-  Memory accesses are coalesced\index{coalesced memory accesses} \cite{CUDA_ProgGuide} in order to
+  Memory accesses are coalesced\index{GPU!coalesced memory accesses} \cite{CUDA_ProgGuide} in order to
   provide the best performance for such memory-bound kernels.
 \item[Step 2] (``Local copies''):~data are copied from
   local $R$-matrices to temporary arrays ($U$, $V$) and to $\Re^{O}$.
@@ -917,7 +917,7 @@ one C2050 (Fermi) GPU, located at
  UPMC (Universit\'e Pierre et Marie Curie, Paris, France). 
 As a remark, the execution times measured on the C2050 would be the same 
 on the C2070 and on  the C2075, the only difference between these GPUs 
-being their memory size and their TDP (Thermal Design Power)\index{TDP (Thermal Design Power)}. 
+being their memory size and their TDP (Thermal Design Power)\index{TDP (thermal design power)}. 
 We emphasize that the execution times correspond to the
 complete propagation for all six energies of the large case (see
 Table~\ref{data-sets}), that is to say to the complete execution of