Type of Document Thesis Author Brailsford, Frank Steve Author's Email Address email@example.com URN etd-04132010-234917 Title SPRNG gets a Normal Number Generator Degree Master of Science Department Computer Science, Department of Advisory Committee
Advisor Name Title Michael Mascagni Committee Chair Ashok Srinivasan Committee Member Xiuwen Liu Committee Member Keywords
- Random Number Generation
Date of Defense 2010-03-04 Availability unrestricted AbstractThis thesis presents and evaluates a new algorithm which generates random numbers.
The algorithm uses a Number Theory class of numbers called Normal Numbers. Normal
Numbers consist of an innite sequence of digits which are uniformly distributed
in all sequence lengths.
The algorithm is then integrated into the SPRNG package with some ideas as to
how it can be parallelized. Finally, the performance of this algorithm is evaluated
using a standard test suite. This new algorithm is compared with similar, known
good, generators using the spectral test and also as the random number generator in
a Monte Carlo algorithm. The generator is shown to work well in all tests and to
produce value with moderately good speed.
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