From: Arnaud Giersch Date: Tue, 6 Jan 2015 12:00:10 +0000 (+0100) Subject: Correct definition for F in algorithmic complexity. X-Git-Tag: pdsec15_submission~1 X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/mpi-energy2.git/commitdiff_plain/9d8fb958492a746f41e38f810c99fb065ca9300e?ds=inline Correct definition for F in algorithmic complexity. --- diff --git a/Heter_paper.tex b/Heter_paper.tex index 55d72f6..a9a1e6d 100644 --- a/Heter_paper.tex +++ b/Heter_paper.tex @@ -731,9 +731,9 @@ cluster composed of four different types of nodes having the characteristics presented in Table~\ref{table:platform}, it takes on average \np[ms]{0.04} for 4 nodes and \np[ms]{0.15} on average for 144 nodes to compute the best scaling factors vector. The algorithm complexity is $O(F\cdot N)$, where $F$ is the -number of iterations and $N$ is the number of computing nodes. The algorithm -needs from 12 to 20 iterations to select the best vector of frequency scaling -factors that gives the results of the next sections. +maximum number of available frequencies, and $N$ is the number of computing +nodes. The algorithm needs from 12 to 20 iterations to select the best vector of +frequency scaling factors that gives the results of the next sections. \begin{table}[!t] \caption{Heterogeneous nodes characteristics}