From: lilia Date: Mon, 28 Apr 2014 10:23:36 +0000 (+0200) Subject: 28-04-2014 X-Git-Tag: hpcc2014_submission~47 X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/hpcc2014.git/commitdiff_plain/3efa8416208cc62a83dcb1ba7a97707eb62f1dbf?ds=inline;hp=-c 28-04-2014 --- 3efa8416208cc62a83dcb1ba7a97707eb62f1dbf diff --git a/hpcc.tex b/hpcc.tex index 47480f8..e4c77d3 100644 --- a/hpcc.tex +++ b/hpcc.tex @@ -419,17 +419,17 @@ u =0 \text{~on~} \Gamma =\partial\Omega \right. \label{eq:02} \end{equation} -where $\nabla^2$ is the Laplace operator, $f$ and $u$ are real-valued functions, and $\Omega=[0,1]^3$. The spatial discretization with a finite difference scheme reduces problem~(\ref{eq:02}) to a system of sparse linear equations. The general iteration scheme of our multisplitting method in a 3D domain using a seven point stencil could be written as +where $\nabla^2$ is the Laplace operator, $f$ and $u$ are real-valued functions, and $\Omega=[0,1]^3$. The spatial discretization with a finite difference scheme reduces problem~(\ref{eq:02}) to a system of sparse linear equations. Our multisplitting method solves the 3D Poisson problem using a seven point stencil whose the general expression could be written as \begin{equation} -\begin{array}{ll} -u^{k+1}(x,y,z)= & u^k(x,y,z) - \frac{1}{6}\times\\ - & (u^k(x-1,y,z) + u^k(x+1,y,z) + \\ - & u^k(x,y-1,z) + u^k(x,y+1,z) + \\ - & u^k(x,y,z-1) + u^k(x,y,z+1)), +\begin{array}{l} +u(x-1,y,z) + u(x,y-1,z) + u(x,y,z-1)\\+u(x+1,y,z)+u(x,y+1,z)+u(x,y,z+1) \\ -6u(x,y,z)=h^2f(x,y,z) +%u(x,y,z)= & \frac{1}{6}\times [u(x-1,y,z) + u(x+1,y,z) + \\ + % & u(x,y-1,z) + u(x,y+1,z) + \\ + % & u(x,y,z-1) + u(x,y,z+1) - \\ & h^2f(x,y,z)], \end{array} \label{eq:03} \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. +where $h$ is the distance between two adjacent elements in the spatial discretization scheme and 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 or in distant clusters with which it shares data at sub-domain boundaries.