Numerical simulations in computational physics, biology, and finance, often require the use of high quality and efficient parallel random number generators. We design and optimi...
David A. Bader, Aparna Chandramowlishwaran, Virat ...
Parallel computing has been touted as the pinnacle of high performance digital computing by many. However, many problems remain intractable using deterministic algorithms. Randomiz...
Stochastic simulations and other scientific applications that depend on random numbers are increasingly implemented in a parallelized manner in programmable logic. High-quality ps...
Abstract. Financial applications are one of many fields where a multivariate Gaussian random number generator plays a key role in performing computationally extensive simulations. ...
There is a large gap between the theory and practice for random number generation. For example, on most operating systems, using /dev/random to generate a 256-bit AES key is highl...