From: Raphael Couturier Date: Thu, 10 Nov 2011 20:27:10 +0000 (+0100) Subject: new X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/prng_gpu.git/commitdiff_plain/4f77fbaca003dceaba9d6c5f8c6695327b1e2113 new --- diff --git a/prng_gpu.tex b/prng_gpu.tex index 19adf22..82a4927 100644 --- a/prng_gpu.tex +++ b/prng_gpu.tex @@ -74,11 +74,11 @@ numbers inside a GPU when a scientific application runs in a GPU. That is why we 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 @@ -955,13 +955,14 @@ Devaney's formulation of a chaotic behavior. \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}