  Conventional random number generators provide the speed but not necessarily
the high quality output streams needed for large-scale stochastic simulations.
Cryptographically-based generators, on the other hand, provide superior quality
output but are often deemed too slow to be practical for use in large
simulations. We combine these two approaches to construct a family of hybrid
generators that permit users to choose the desired tradeoff between quality and
speed for a given application. We demonstrate the effectiveness, performance,
and practicality of this approach using a standard battery of tests, which show
that high quality streams of random numbers can be obtained at a cost
comparable to that of fast conventional generators.
