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GTC ON-DEMAND

Developer - Algorithms
Presentation
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Efficient implementation of Mersenne Twister MT19937 Random Number Generator on the GPU
Abstract:
Described will be a novel approach to implementation of Mersenne Twister MT19937 Random Number Generator on the GPUs. MT19937 is one of the most widely used PRNG for the Monte Carlo simulations, due to its speed and very good statistical properties. It was believed, however, that it does not parallelize well, and parallel implementations of it are rare (for example, Intel MKL library provides only single-threaded implementation of MT19937). Our implementation proves the opposite, being much faster than both cuRAND XORWOW and MTGP (Mersenne Twister for Graphics Processors) on Tesla K20X. Presented algorithm is being incorporated in the upcoming release of cuRAND.
 
Topics:
Developer - Algorithms
Type:
Poster
Event:
GTC Silicon Valley
Year:
2013
Session ID:
P3132
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