From c1552aed123e4154c36983b72f5abd7c1578091f Mon Sep 17 00:00:00 2001 From: raphael couturier Date: Sat, 11 Oct 2014 20:47:10 +0200 Subject: [PATCH] new --- paper.tex | 16 +++++++++++++++- 1 file changed, 15 insertions(+), 1 deletion(-) diff --git a/paper.tex b/paper.tex index 4d59b93..a4c9b26 100644 --- a/paper.tex +++ b/paper.tex @@ -1035,7 +1035,21 @@ the number of iterations. So, the overall benefit of using TSIRM is interesting. \end{table*} -In Table~\ref{tab:04}, some experiments with example ex54 on the Curie architecture are reported. +In Table~\ref{tab:04}, some experiments with example ex54 on the Curie +architecture are reported. For this application, we fixed $\alpha=0.6$. As it +can be seen in that Table, the size of the problem has a strong influence on the +number of iterations to reach the convergence. That is why we have preferred to +change the threshold. If we set it to $1e-3$ as with the previous application, +only one iteration is necessray to reach the convergence. So Table~\ref{tab:04} +shows the results of differents executions with differents number of cores and +differents thresholds. As with the previous example, we can observe that TSIRM +is faster than FGMRES. The ratio greatly depends on the number of iterations for +FMGRES to reach the threshold. The greater the number of iterations to reach the +convergence is, the better the ratio between our algorithm and FMGRES is. This +experiment is also a weak scaling with approximately $25,000$ components per +core. It can also be observed that the difference between CGLS and LSQR is not +significant. Both can be good but it seems not possible to know in advance which +one will be the best. \begin{table*}[htbp] -- 2.39.5