PRNGs for Langevin simulations of biomolecules fully implemented on
GPU. Performance of the GPU versions are far better than those obtained with a
CPU, and these PRNGs succeed to pass the {\it BigCrush} battery of TestU01.
-However the evaluations of the proposed PRNGs are only statistical.
+However the evaluations of the proposed PRNGs are only statistical ones.
Authors of~\cite{conf/fpga/ThomasHL09} have studied the implementation of some
PRNGs on diferrent computing architectures: CPU, field-programmable gate array
(FPGA), GPU and massively parallel processor. This study is interesting because
-it shows the performance of the same PRNGs on different architeture. For
+it shows the performance of the same PRNGs on different architectures. For
example, the FPGA is globally the fastest architecture and it is also the
efficient one because it provides the fastest number of generated random numbers
per joule. Concerning the GPU, authors can generate betweend 11 and 16GSample/s
