\begin{tabular}{r c }
\hline
Grid & 2x16\\ %\hline
- Network & N2 : bw=1Gbs - lat=5E-05 \\ %\hline
+ Network & N2 : bw=1Gbs - lat=5.10$^{-5}$ \\ %\hline
Input matrix size & N$_{x}$ = 150 x 150 x 150\\ \hline
\end{tabular}
Table 6 : CPU Power impact \\
\hline
Grid & 2x50 totaling 100 processors\\ %\hline
Processors & 1 GFlops to 1.5 GFlops\\
- Intra-Network & bw=1.25 Gbits - lat=5E-05 \\ %\hline
- Inter-Network & bw=5 Mbits - lat=2E-02\\
+ Intra-Network & bw=1.25 Gbits - lat=5.10$^{-5}$ \\ %\hline
+ Inter-Network & bw=5 Mbits - lat=2.10$^{-2}$\\
Input matrix size & N$_{x}$ = From 62 to 150\\ %\hline
- Residual error precision: 10$^{-5}$ to 10$^{-9}$\\ \hline \\
+ Residual error precision & 10$^{-5}$ to 10$^{-9}$\\ \hline \\
\end{tabular}
\end{footnotesize}
simulator tool with different problem size. The relative gains greater
than 1 between the two algorithms have been captured after each step of
the test. Table I below has recorded the best grid configurations
-allowing a multiplitting method time more than 2.5 times lower than
-classical GMRES execution and convergence time. The finding thru this
-experimentation is the tolerance of the multisplitting method under a
-low speed network that we encounter usually with distant clusters thru the
-internet.
+allowing the multisplitting method execution time more performant 2.5 times than
+the classical GMRES execution and convergence time. The experimentation has demonstrated the relative multisplitting algorithm tolerance when using a low speed network that we encounter usually with distant clusters thru the internet.
% use the same column width for the following three tables
\newlength{\mytablew}\settowidth{\mytablew}{\footnotesize\np{E-11}}
the classical GMRES}
\label{"Table 7"}
- \begin{mytable}{6}
- \hline
- bandwidth (Mbit/s)
- & 5 & 5 & 5 & 5 & 5 \\
- \hline
- latency (ms)
- & 20 & 20 & 20 & 20 & 20 \\
- \hline
- power (GFlops)
- & 1 & 1 & 1 & 1.5 & 1.5 \\
- \hline
- size (N)
- & 62 & 62 & 62 & 100 & 100 \\
- \hline
- Precision
- & \np{E-5} & \np{E-8} & \np{E-9} & \np{E-11} & \np{E-11} \\
- \hline
- Relative gain
- & 2.52 & 2.55 & 2.52 & 2.57 & 2.54 \\
- \hline
- \end{mytable}
-
- \smallskip
-
- \begin{mytable}{6}
+ \begin{mytable}{11}
\hline
bandwidth (Mbit/s)
- & 50 & 50 & 50 & 50 & 50 \\
+ & 5 & 5 & 5 & 5 & 5 & 50 & 50 & 50 & 50 & 50 \\
\hline
latency (ms)
- & 20 & 20 & 20 & 20 & 20 \\
+ & 20 & 20 & 20 & 20 & 20 & 20 & 20 & 20 & 20 & 20 \\
\hline
power (GFlops)
- & 1.5 & 1.5 & 1 & 1.5 & 1.5 \\
+ & 1 & 1 & 1 & 1.5 & 1.5 & 1.5 & 1.5 & 1 & 1.5 & 1.5 \\
\hline
size (N)
- & 110 & 120 & 130 & 140 & 150 \\
+ & 62 & 62 & 62 & 100 & 100 & 110 & 120 & 130 & 140 & 150 \\
\hline
Precision
- & \np{E-11} & \np{E-11} & \np{E-11} & \np{E-11} & \np{E-11}\\
+ & \np{E-5} & \np{E-8} & \np{E-9} & \np{E-11} & \np{E-11} & \np{E-11} & \np{E-11} & \np{E-11} & \np{E-11} & \np{E-11}\\
\hline
Relative gain
- & 2.53 & 2.51 & 2.58 & 2.55 & 2.54 \\
+ & 2.52 & 2.55 & 2.52 & 2.57 & 2.54 & 2.53 & 2.51 & 2.58 & 2.55 & 2.54 \\
\hline
\end{mytable}
\end{table}