spell check

diff --git a/prng_gpu.tex b/prng_gpu.tex
index 7d94e0c7e3fa6fbffc4698764646a59f6849838b..6c6c980902aed3f6118d9295261631f4b886fffd 100644 (file)
--- a/prng_gpu.tex
+++ b/prng_gpu.tex
@@ -135,7 +135,7 @@ allows us to generate almost 20 billion of pseudorandom numbers per second.
 Furthermore, we show that the proposed post-treatment preserves the
 cryptographical security of the inputted PRNG, when this last has such a 
 property.
 Furthermore, we show that the proposed post-treatment preserves the
 cryptographical security of the inputted PRNG, when this last has such a 
 property.

-Last, but not least, we propose a rewritting of the Blum-Goldwasser asymmetric
+Last, but not least, we propose a rewriting of the Blum-Goldwasser asymmetric

 key encryption protocol by using the proposed method.
 
 The remainder of this paper  is organized as follows. In Section~\ref{section:related
 key encryption protocol by using the proposed method.
 
 The remainder of this paper  is organized as follows. In Section~\ref{section:related


@@ -536,7 +536,7 @@ x^0 \in \llbracket 0, 2^\mathsf{N}-1 \rrbracket, S \in \llbracket 0, 2^\mathsf{N
 \label{equation Oplus}
 \end{equation}
 where $\oplus$ is for the bitwise exclusive or between two integers. 
 \label{equation Oplus}
 \end{equation}
 where $\oplus$ is for the bitwise exclusive or between two integers. 

-This rewritting can be understood as follows. The $n-$th term $S^n$ of the
+This rewriting can be understood as follows. The $n-$th term $S^n$ of the

 sequence $S$, which is an integer of $\mathsf{N}$ binary digits, presents
 the list of cells to update in the state $x^n$ of the system (represented
 as an integer having $\mathsf{N}$ bits too). More precisely, the $k-$th 
 sequence $S$, which is an integer of $\mathsf{N}$ binary digits, presents
 the list of cells to update in the state $x^n$ of the system (represented
 as an integer having $\mathsf{N}$ bits too). More precisely, the $k-$th 


@@ -950,7 +950,7 @@ NumThreads: number of threads\;}
 
 Algorithm~\ref{algo:gpu_kernel}  presents a naive  implementation of the proposed  PRNG on
 GPU.  Due to the available  memory in the  GPU and the number  of threads
 
 Algorithm~\ref{algo:gpu_kernel}  presents a naive  implementation of the proposed  PRNG on
 GPU.  Due to the available  memory in the  GPU and the number  of threads

-used simultenaously,  the number  of random numbers  that a thread  can generate
+used simultaneously,  the number  of random numbers  that a thread  can generate

 inside   a    kernel   is   limited  (\emph{i.e.},    the    variable   \texttt{n}   in
 algorithm~\ref{algo:gpu_kernel}). For instance, if  $100,000$ threads are used and
 if $n=100$\footnote{in fact, we need to add the initial seed (a 32-bits number)},
 inside   a    kernel   is   limited  (\emph{i.e.},    the    variable   \texttt{n}   in
 algorithm~\ref{algo:gpu_kernel}). For instance, if  $100,000$ threads are used and
 if $n=100$\footnote{in fact, we need to add the initial seed (a 32-bits number)},


@@ -1255,7 +1255,7 @@ lesser than $2^{16}$.  So in practice we can choose prime numbers around
 indistinguishable    bits    is    lesser    than   or    equals    to
 $log_2(log_2(M))$). In other words, to generate a  32-bits number, we need to use
 8 times  the BBS  algorithm with possibly different  combinations of  $M$. This
 indistinguishable    bits    is    lesser    than   or    equals    to
 $log_2(log_2(M))$). In other words, to generate a  32-bits number, we need to use
 8 times  the BBS  algorithm with possibly different  combinations of  $M$. This

-approach is  not sufficient to be able to pass  all the TestU01,
+approach is  not sufficient to be able to pass  all the tests of TestU01,

 as small values of  $M$ for the BBS  lead to
   small periods. So, in  order to add randomness  we have proceeded with
 the followings  modifications. 
 as small values of  $M$ for the BBS  lead to
   small periods. So, in  order to add randomness  we have proceeded with
 the followings  modifications. 


@@ -1344,7 +1344,7 @@ variability.  In these operations, we make twice a left shift of $t$ of \emph{at
   most}  3 bits,  represented by  \texttt{shift} in  the algorithm,  and  we put
 \emph{exactly} the \texttt{shift}  last bits from a BBS  into the \texttt{shift}
 last bits of $t$. For this, an array named \texttt{array\_shift}, containing the
   most}  3 bits,  represented by  \texttt{shift} in  the algorithm,  and  we put
 \emph{exactly} the \texttt{shift}  last bits from a BBS  into the \texttt{shift}
 last bits of $t$. For this, an array named \texttt{array\_shift}, containing the

-correspondance between the  shift and the number obtained  with \texttt{shift} 1
+correspondence between the  shift and the number obtained  with \texttt{shift} 1

 to make the \texttt{and} operation is used. For example, with a left shift of 0,
 we  make an  and operation  with 0,  with  a left  shift of  3, we  make an  and
 operation with 7 (represented by 111 in binary mode).
 to make the \texttt{and} operation is used. For example, with a left shift of 0,
 we  make an  and operation  with 0,  with  a left  shift of  3, we  make an  and
 operation with 7 (represented by 111 in binary mode).