accurate results which are difficult or even impossible to obtain in a
physical platform by exploiting the flexibility of the simulator on the
computing units clusters and the network structure design. Our
accurate results which are difficult or even impossible to obtain in a
physical platform by exploiting the flexibility of the simulator on the
computing units clusters and the network structure design. Our
perspectives on experimentations for running the algorithm on a
simulated large scale growing environment and with larger problem size.
perspectives on experimentations for running the algorithm on a
simulated large scale growing environment and with larger problem size.
that it was difficult to have a combination which gives an efficiency of
asynchronous below \np[\%]{80}. Indeed, for a matrix size of 62 elements, equality
between the performance of the two modes (synchronous and asynchronous) is
that it was difficult to have a combination which gives an efficiency of
asynchronous below \np[\%]{80}. Indeed, for a matrix size of 62 elements, equality
between the performance of the two modes (synchronous and asynchronous) is
challenge an efficiency by \np[\%]{78} with a matrix size of 100 points, it was
necessary to degrade the inter cluster network bandwidth from 5 to 2 Mbit/s.
challenge an efficiency by \np[\%]{78} with a matrix size of 100 points, it was
necessary to degrade the inter cluster network bandwidth from 5 to 2 Mbit/s.
\setcounter{numberedCntD}{\theenumi}
\end{enumerate}
Our results have shown that in certain conditions, asynchronous mode is
\setcounter{numberedCntD}{\theenumi}
\end{enumerate}
Our results have shown that in certain conditions, asynchronous mode is