Many scientific and engineering applications, which are increasingly being ported from software to reconfigurable platforms, require Gaussian-distributed random numbers. Thus, the...
Hassan Edrees, Brian Cheung, McCullen Sandora, Dav...
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...
— The paper presents a simple stochastic model of a True Random Number Generator, which extracts randomness from the tracking jitter of a phase-locked loop. The existence of such...