X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/prng_gpu.git/blobdiff_plain/80c5c05c07373d50d1af355c7a25a336a12f7d73..0cafd2bf1c7bf4758d8f1aa902d08d880419b67d:/prng_gpu.tex

diff --git a/prng_gpu.tex b/prng_gpu.tex
index 00752c7..74b78a9 100644
--- a/prng_gpu.tex
+++ b/prng_gpu.tex
@@ -1082,7 +1082,7 @@ As a  comparison,   Listing~\ref{algo:seqCIPRNG}  leads   to the  generation of
 
 In Figure~\ref{fig:time_bbs_gpu}  we highlight the performances  of the optimized
 BBS-based  PRNG on GPU. On the  Tesla C1060 we
-obtain approximately 1.8GSample/s and on the GTX 280 about 1.6GSample/s, which is
+obtain approximately 700MSample/s and on the GTX 280 about 670MSample/s, which is
 obviously slower than the xorlike-based PRNG on GPU. However, we will show in the 
 next sections that 
 this new PRNG has a strong level of security, which is necessary paid by a speed