From 87062e3e1ac002d9b4c2175d7844aff13f17404e Mon Sep 17 00:00:00 2001 From: lilia Date: Thu, 7 May 2015 22:06:13 +0200 Subject: [PATCH] Corrections dans section 5 --- paper.tex | 27 +++++++++++++-------------- 1 file changed, 13 insertions(+), 14 deletions(-) diff --git a/paper.tex b/paper.tex index efbda8a..d5a458c 100644 --- a/paper.tex +++ b/paper.tex @@ -433,10 +433,10 @@ It should also be noticed that both solvers have been executed with the SimGrid %%%%%%%%%%%%%%%%%%%%%%%%% %%%%%%%%%%%%%%%%%%%%%%%%% -\section{Experimental Results} +\section{Experimental results} \label{sec:expe} -In this section, experiments for both Multisplitting algorithms are reported. First the 3D Poisson problem used in our experiments is described. +In this section, experiments for both multisplitting algorithms are reported. First the 3D Poisson problem used in our experiments is described. \subsection{The 3D Poisson problem} \label{3dpoisson} @@ -473,9 +473,9 @@ have been chosen for the study in this paper. \\ \textbf{Step 2}: Collect the software materials needed for the experimentation. In our case, we have two variants algorithms for the resolution of the -3D-Poisson problem: (1) using the classical GMRES; (2) and the Multisplitting -method. In addition, the Simgrid simulator has been chosen to simulate the -behaviors of the distributed applications. Simgrid is running in a virtual +3D-Poisson problem: (1) using the classical GMRES; (2) and the multisplitting +method. In addition, the SimGrid simulator has been chosen to simulate the +behaviors of the distributed applications. SimGrid is running in a virtual machine on a simple laptop. \\ \textbf{Step 3}: Fix the criteria which will be used for the future @@ -484,10 +484,10 @@ on the one hand the algorithm execution mode (synchronous and asynchronous) and on the other hand the execution time and the number of iterations to reach the convergence. \\ \textbf{Step 4 }: Set up the different grid testbed environments that will be -simulated in the simulator tool to run the program. The following architecture -has been configured in Simgrid : 2x16, 4x8, 4x16, 8x8 and 2x50. The first number +simulated in the simulator tool to run the program. The following architectures +have been configured in SimGrid : 2$\times$16, 4$\times$8, 4$\times$16, 8$\times$8 and 2$\times$50. The first number represents the number of clusters in the grid and the second number represents -the number of hosts (processors/cores) in each cluster. The network has been +the number of hosts (processors/cores) in each cluster. The network has been designed to operate with a bandwidth equals to 10Gbits (resp. 1Gbits/s) and a latency of 8.10$^{-6}$ seconds (resp. 5.10$^{-5}$) for the intra-clusters links (resp. inter-clusters backbone links). \\ @@ -499,8 +499,7 @@ input data. \\ \textbf{Step 6} : Collect and analyze the output results. -\subsection{Factors impacting distributed applications performance in -a grid environment} +\subsection{Factors impacting distributed applications performance in a grid environment} When running a distributed application in a computational grid, many factors may have a strong impact on the performance. First of all, the architecture of the @@ -513,10 +512,10 @@ Another important factor impacting the overall performance of the application is the network configuration. Two main network parameters can modify drastically the program output results: \begin{enumerate} -\item the network bandwidth (bw=bits/s) also known as "the data-carrying +\item the network bandwidth ($bw$ in bits/s) also known as "the data-carrying capacity" of the network is defined as the maximum of data that can transit from one point to another in a unit of time. -\item the network latency (lat : microsecond) defined as the delay from the +\item the network latency ($lat$ in microseconds) defined as the delay from the start time to send a simple data from a source to a destination. \end{enumerate} Upon the network characteristics, another impacting factor is the volume of data exchanged between the nodes in the cluster @@ -527,8 +526,8 @@ and between distant clusters. This parameter is application dependent. on the other hand, the "inter-network" which is the backbone link between clusters. In practice, these two networks have different speeds. The intra-network generally works like a high speed local network with a - high bandwith and very low latency. In opposite, the inter-network connects - clusters sometime via heterogeneous networks components throuth internet with + high bandwidth and very low latency. In opposite, the inter-network connects + clusters sometime via heterogeneous networks components through internet with a lower speed. The network between distant clusters might be a bottleneck for the global performance of the application. -- 2.39.5