RCE : Quelques corrections

[rce2015.git] / paper.tex

diff --git a/paper.tex b/paper.tex
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--- a/paper.tex
+++ b/paper.tex
@@ -92,14 +92,27 @@
 %% Lilia Ziane Khodja: Department of Aerospace \& Mechanical Engineering\\ Non Linear Computational Mechanics\\ University of Liege\\ Liege, Belgium. Email: l.zianekhodja@ulg.ac.be
 
 \begin{abstract}
 %% Lilia Ziane Khodja: Department of Aerospace \& Mechanical Engineering\\ Non Linear Computational Mechanics\\ University of Liege\\ Liege, Belgium. Email: l.zianekhodja@ulg.ac.be
 
 \begin{abstract}

-ABSTRACT
+  The behavior of multicore applications is always a challenge to predict, especially with a new architecture for which no experiment has been performed. With some applications, it is difficult, if not impossible, to build accurate performance models. That is why another solution is to use a simulation tool which allows us to change many parameters of the architecture (network bandwidth, latency, number of processors) and to simulate the execution of such applications. We have decided to use SimGrid as it enables to benchmark MPI applications.
+
+In this paper, we focus our attention on two parallel iterative algorithms based
+on the  Multisplitting algorithm  and we  compare them  to the  GMRES algorithm.
+These algorithms  are used to  solve libear  systems. Two different  variantsof the Multisplitting are
+studied: one  using synchronoous  iterations and  another one  with asynchronous
+iterations. For each algorithm we have  tested different parameters to see their
+influence.  We strongly  recommend people  interested  by investing  into a  new
+expensive  hardware  architecture  to   benchmark  their  applications  using  a
+simulation tool before.
+
+  
+
+  

 \end{abstract}
 
 \keywords{Algorithm; distributed; iterative; asynchronous; simulation; simgrid; performance}
 
 \maketitle
 
 \end{abstract}
 
 \keywords{Algorithm; distributed; iterative; asynchronous; simulation; simgrid; performance}
 
 \maketitle
 

-\section{Introduction}
+\section{Introduction} 

 
 \section{The asynchronous iteration model}
 
 
 \section{The asynchronous iteration model}
 


@@ -196,17 +209,17 @@ The algorithm in Figure~\ref{alg:02} includes the procedure of the residual mini
 \subsection{Simulation of two-stage methods using SimGrid framework}
 \label{sec:04.02}
 
 \subsection{Simulation of two-stage methods using SimGrid framework}
 \label{sec:04.02}
 

-One of our objectives when simulating the application in SIMGRID is, as in real life, to get accurate results (solutions of the problem) but also ensure the test reproducibility under the same conditions.According our experience, very few modifications are required to adapt a MPI program to run in SIMGRID simulator using SMPI (Simulator MPI).The first modification is to include SMPI libraries and related header files (smpi.h). The second and important modification is to eliminate all global variables in moving them to local subroutine or using a Simgrid selector called "runtime automatic switching" (smpi/privatize\_global\_variables). Indeed, global variables can generate side effects on runtime between the threads running in the same process, generated by the Simgrid to simulate the grid environment.The last modification on the MPI program pointed out for some cases, the review of the sequence of the MPI\_Isend, MPI\_Irecv and MPI\_Waitall instructions which might cause an infinite loop.     
+One of our objectives when simulating the application in SIMGRID is, as in real life, to get accurate results (solutions of the problem) but also ensure the test reproducibility under the same conditions. According our experience, very few modifications are required to adapt a MPI program to run in SIMGRID simulator using SMPI (Simulator MPI).The first modification is to include SMPI libraries and related header files (smpi.h). The second and important modification is to eliminate all global variables in moving them to local subroutine or using a Simgrid selector called "runtime automatic switching" (smpi/privatize\_global\_variables). Indeed, global variables can generate side effects on runtime between the threads running in the same process, generated by the Simgrid to simulate the grid environment.The last modification on the MPI program pointed out for some cases, the review of the sequence of the MPI\_Isend, MPI\_Irecv and MPI\_Waitall instructions which might cause an infinite loop.     

 
 
 \paragraph{SIMGRID Simulator parameters}
 
 \begin{itemize}
 
 
 \paragraph{SIMGRID Simulator parameters}
 
 \begin{itemize}

-       \item HOSTFILE: Hosts description file.
-       \item PLATFORM: File describing the platform architecture : clusters (CPU power,
+       \item hostfile: Hosts description file.
+       \item plarform: File describing the platform architecture : clusters (CPU power,

 \dots{}), intra cluster network description, inter cluster network (bandwidth bw,
 \dots{}), intra cluster network description, inter cluster network (bandwidth bw,

-lat latency, \dots{}).
-       \item ARCHI   : Grid computational description (Number of clusters, Number of 
+latency lat, \dots{}).
+       \item archi   : Grid computational description (Number of clusters, Number of 

 nodes/processors for each cluster). 
 \end{itemize}
 
 nodes/processors for each cluster). 
 \end{itemize}
 


@@ -216,43 +229,38 @@ In addition, the following arguments are given to the programs at runtime:
 \begin{itemize}
        \item Maximum number of inner and outer iterations;
        \item Inner and outer precisions;
 \begin{itemize}
        \item Maximum number of inner and outer iterations;
        \item Inner and outer precisions;

-       \item Matrix size (NX, NY and NZ);
+       \item Matrix size (N$_{x}$, N$_{y}$ and N$_{z}$);

        \item Matrix diagonal value = 6.0;
        \item Execution Mode: synchronous or asynchronous.
 \end{itemize}
 
        \item Matrix diagonal value = 6.0;
        \item Execution Mode: synchronous or asynchronous.
 \end{itemize}
 

-At last, note that the two solver algorithms have been executed with the Simgrid selector --cfg=smpi/running\_power which determine the computational power (here 19GFlops) of the simulator host machine.  
+At last, note that the two solver algorithms have been executed with the Simgrid selector -cfg=smpi/running\_power which determine the computational power (here 19GFlops) of the simulator host machine.  

 
 %%%%%%%%%%%%%%%%%%%%%%%%%
 %%%%%%%%%%%%%%%%%%%%%%%%%
 
 
 %%%%%%%%%%%%%%%%%%%%%%%%%
 %%%%%%%%%%%%%%%%%%%%%%%%%
 

-\section{Experimental, Results and Comments}
+\section{Experimental Results}

 
 
 \subsection{Setup study and Methodology}
 
 To conduct our study, we have put in place the following methodology 
 
 
 \subsection{Setup study and Methodology}
 
 To conduct our study, we have put in place the following methodology 

-which can be reused with any grid-enabled applications.
+which can be reused for any grid-enabled applications.

 
 \textbf{Step 1} : Choose with the end users the class of algorithms or 
 the application to be tested. Numerical parallel iterative algorithms 
 
 \textbf{Step 1} : Choose with the end users the class of algorithms or 
 the application to be tested. Numerical parallel iterative algorithms 

-have been chosen for the study in the paper. 
+have been chosen for the study in this paper. \\

 
 \textbf{Step 2} : Collect the software materials needed for the 
 
 \textbf{Step 2} : Collect the software materials needed for the 

-experimentation. In our case, we have three variants algorithms for the 
-resolution of three 3D-Poisson problem: (1) using the classical GMRES alias Algo-1 in this 
-paper, (2) using the multisplitting method alias Algo-2 and (3) an 
-enhanced version of the multisplitting method as Algo-3. In addition, 
-SIMGRID simulator has been chosen to simulate the behaviors of the 
-distributed applications. SIMGRID is running on the Mesocentre 
-datacenter in Franche-Comte University but also in a virtual 
-machine on a laptop.
+experimentation. In our case, we have two variants algorithms for the 
+resolution of three 3D-Poisson problem: (1) using the classical GMRES (Algo-1)(2) and the multisplitting method (Algo-2). In addition, SIMGRID simulator has been chosen to simulate the behaviors of the 
+distributed applications. SIMGRID is running on the Mesocentre datacenter in Franche-Comte University but also in a virtual machine on a laptop. \\

 
 \textbf{Step 3} : Fix the criteria which will be used for the future 
 results comparison and analysis. In the scope of this study, we retain 
 in one hand the algorithm execution mode (synchronous and asynchronous) 
 and in the other hand the execution time and the number of iterations of 
 
 \textbf{Step 3} : Fix the criteria which will be used for the future 
 results comparison and analysis. In the scope of this study, we retain 
 in one hand the algorithm execution mode (synchronous and asynchronous) 
 and in the other hand the execution time and the number of iterations of 

-the application before obtaining the convergence.
+the application before obtaining the convergence. \\

 
 \textbf{Step 4 }: Setup up the different grid testbeds environment 
 which will be simulated in the simulator tool to run the program. The 
 
 \textbf{Step 4 }: Setup up the different grid testbeds environment 
 which will be simulated in the simulator tool to run the program. The 


@@ -261,15 +269,15 @@ grid containing 2 clusters with 16 hosts (processors/cores) each -, 4x8,
 4x16, 8x8 and 2x50. The network has been designed to operate with a 
 bandwidth equals to 10Gbits (resp. 1Gbits/s) and a latency of 8E-6 
 microseconds (resp. 5E-5) for the intra-clusters links (resp. 
 4x16, 8x8 and 2x50. The network has been designed to operate with a 
 bandwidth equals to 10Gbits (resp. 1Gbits/s) and a latency of 8E-6 
 microseconds (resp. 5E-5) for the intra-clusters links (resp. 

-inter-clusters backbone links).
+inter-clusters backbone links). \\

 
 

-\textbf{Step 5}: Process an extensive and comprehensive testings 
+\textbf{Step 5}: Conduct an extensive and comprehensive testings 

 within these configurations in varying the key parameters, especially 
 the CPU power capacity, the network parameters and also the size of the 
 within these configurations in varying the key parameters, especially 
 the CPU power capacity, the network parameters and also the size of the 

-input matrix. Note that some parameters should be invariant to allow the 
-comparison like some program input arguments.
+input matrix. Note that some parameters should be fixed to be invariant to allow the 
+comparison like some program input arguments. \\

 
 

-{Step 6} : Collect and analyze the output results.
+\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}