X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/book_gpu.git/blobdiff_plain/cacf1137755cd5d5eba063f453055e49a25d579f..57e564506a8117605eca5b5d80c0f492e6121c12:/BookGPU/Chapters/chapter15/ch15.tex?ds=sidebyside 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