convergence depends on the delay of messages. With synchronous iterations, the
number of iterations is exactly the same than in the sequential mode (if the
parallelization process does not change the algorithm). So the difficulty with
- asynchronous iteratie algorithms comes from the fact it is necessary to run the algorithm
+ asynchronous iterative algorithms comes from the fact it is necessary to run the algorithm
with real data. In fact, from an execution to another the order of messages will
change and the number of iterations to reach the convergence will also change.
According to all the parameters of the platform (number of nodes, power of
- nodes, inter and intra clusrters bandwith and latency, ....) and of the
- algorithm (number of splitting with the multisplitting algorithm), the
- multisplitting code will obtain the solution more or less quickly. Or course,
+ nodes, inter and intra clusrters bandwith and latency, etc.) and of the
+ algorithm (number of splittings with the multisplitting algorithm), the
+ multisplitting code will obtain the solution more or less quickly. Of course,
the GMRES method also depends of the same parameters. As it is difficult to have
access to many clusters, grids or supercomputers with many different network
parameters, it is interesting to be able to simulate the behaviors of
\begin{figure}[!t]
\centering
- \includegraphics[width=60mm,keepaspectratio]{clustering2}
-\caption{Example of two distant clusters of processors.}
+ \includegraphics[width=60mm,keepaspectratio]{clustering}
+\caption{Example of three distant clusters of processors.}
\label{fig:4.1}
\end{figure}
