also provide an efficient PRNG for GPU respecting based on IC. Such devices
allows us to generated almost 20 billions of random numbers per second.
-In order to establish
+In order to establish that our PRNGs are chaotic according to the Devaney's
+formulation, we extend what we have proposed in~\cite{guyeux10}. Moreover, we define a new distance to measure the disorder in the chaos and we prove some interesting properties with this distance.
The rest of this paper is organised as follows. In Section~\ref{section:related
- works} we review some GPU implementions of PRNG. Section~\ref{sec:chaotic
- iterations} gives some basic recalls on Devanay's formation of chaos and
+ works} we review some GPU implementions of PRNG. Section~\ref{section:BASIC RECALLS} gives some basic recalls on Devanay's formation of chaos and
chaotic iterations. In Section~\ref{sec:pseudo-random} the proof of chaos of our
PRNGs is studied. Section~\ref{sec:efficient prng} presents an efficient
implementation of our chaotic PRNG on a CPU. Section~\ref{sec:efficient prng
\label{sec:experiments}
Different experiments have been performed in order to measure the generation
-speed.
-\begin{figure}[t]
+speed. In Figure~\ref{fig:time_gpu} we compare the number of random numbers generated per second.
+
+\begin{figure}[htbp]
\begin{center}
\includegraphics[scale=.7]{curve_time_gpu.pdf}
\end{center}
\caption{Number of random numbers generated per second}
-\label{fig:time_naive_gpu}
+\label{fig:time_gpu}
\end{figure}
