From e0b0623b3df14288688eac62bc06fb36da2a5101 Mon Sep 17 00:00:00 2001 From: lilia Date: Thu, 24 Apr 2014 15:36:55 +0200 Subject: [PATCH 1/1] 24-04-2014bb --- hpcc.tex | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/hpcc.tex b/hpcc.tex index 29eca38..0072a6f 100644 --- a/hpcc.tex +++ b/hpcc.tex @@ -405,7 +405,7 @@ u^{k+1}(x,y,z)= & u^k(x,y,z) - \frac{1}{6}\times\\ \end{equation} where the iteration matrix $A$ of size $N_x\times N_y\times N_z$ of the discretized linear system is sparse, symmetric and positive definite. -The parallel solving of the 3D Poisson problem with our multisplitting method requires a data partitioning of the problem between clusters and between processors within a cluster. We have chosen the 3D partitioning instead of the row-by-row partitioning in order to reduce the data exchanges at sub-domain boundaries. Figure~\ref{fig:4.2} shows an example of the data partitioning of the 3D Poisson problem between two clusters of processors, where each sub-problem is assigned to a processor. In this context, a processor has at most six neighbors within a cluster of in distant clusters with which it shares data at sub-domain boundaries. +The parallel solving of the 3D Poisson problem with our multisplitting method requires a data partitioning of the problem between clusters and between processors within a cluster. We have chosen the 3D partitioning instead of the row-by-row partitioning in order to reduce the data exchanges at sub-domain boundaries. Figure~\ref{fig:4.2} shows an example of the data partitioning of the 3D Poisson problem between two clusters of processors, where each sub-problem is assigned to a processor. In this context, a processor has at most six neighbors within a cluster or in distant clusters with which it shares data at sub-domain boundaries. \begin{figure}[!t] \centering -- 2.39.5