From: Arnaud Giersch <arnaud.giersch@univ-fcomte.fr>
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=sidebyside;hp=--cc

Correct definition for F in algorithmic complexity.
---

9d8fb958492a746f41e38f810c99fb065ca9300e
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}