new

[book_gpu.git] / BookGPU / Chapters / chapter6 / PartieAsync.tex

diff --git a/BookGPU/Chapters/chapter6/PartieAsync.tex b/BookGPU/Chapters/chapter6/PartieAsync.tex
index 0253c9cb30dc36a1b690d8d9e1c4b0c79d8878b2..9edbe8dce065e6dc88be03de3a3c13f02f5b6547 100644 (file)
--- a/BookGPU/Chapters/chapter6/PartieAsync.tex
+++ b/BookGPU/Chapters/chapter6/PartieAsync.tex
@@ -6,7 +6,7 @@ In the previous section, we have seen how to efficiently implement overlap of
 computations (CPU and GPU) with communications (GPU transfers and internode
 communications).  However, we have previously shown that for some parallel
 iterative algorithms, it is sometimes even more efficient to use an asynchronous
 computations (CPU and GPU) with communications (GPU transfers and internode
 communications).  However, we have previously shown that for some parallel
 iterative algorithms, it is sometimes even more efficient to use an asynchronous

-scheme of iterations\index{iterations asynchronous} \cite{HPCS2002,ParCo05,Para10}.  In that case, the nodes do
+scheme of iterations\index{asynchronous iterations} \cite{HPCS2002,ParCo05,Para10}.  In that case, the nodes do

 not wait for each other but they perform their iterations using the last
 external data they have received from the other nodes, even if this
 data was produced \emph{before} the previous iteration on the other nodes.
 not wait for each other but they perform their iterations using the last
 external data they have received from the other nodes, even if this
 data was produced \emph{before} the previous iteration on the other nodes.