International audienceStochastic simulations are often sensitive to the source of randomness that character-izes the statistical quality of their results. Consequently, we need highly reliable Random Number Generators (RNGs) to feed such applications. Recent developments try to shrink the computa-tion time by relying more and more General Purpose Graphics Processing Units (GP-GPUs) to speed-up stochastic simulations. Such devices bring new parallelization possibilities, but they also introduce new programming difficulties. Since RNGs are at the base of any stochastic simulation, they also need to be ported to GP-GPU. There is still a lack of well-designed implementations of quality-proven RNGs on GP-GPU platforms. In this paper, we introduc...
Version 3 is the same as version 2 but only the resulting PDF was uploaded, to avoid this bug: http:...
Monte Carlo methods provide approximate numerical solutions to problems that would be difficult or i...
We provide a review of the state of the art on the design and implementation of random number genera...
International audienceStochastic simulations are often sensitive to the source of randomness that ch...
International audienceStochastic simulations are often sensitive to the randomness source that chara...
International audienceParallel stochastic simulations tend to exploit more and more computing power ...
The race to computing power increases every day in the simulation community. A few years ago, scient...
International audienceRandom number generation is a key element of stochastic simulations. It has be...
Monte Carlo methods rely on sequences of random numbers to obtain solutions to many problems in scie...
This work considers the deployment of pseudo-random number generators (PRNGs) on graphics processing...
The future of high-performance computing is aligning itself towards the efficient use of highly para...
Abstract EFFICIENT RANDOM NUMBER GENERATION FOR FERMI CLASS GPUs by NIRODHA ABEYWARDANA JAN 2012 Adv...
International audienceRandom number generation is a key element of stochastic simulations. It has be...
Monte Carlo methods rely on sequences of random numbers to obtain solutions to many problems in scie...
High-performance streams of (pseudo) random numbers are crucial for the efficient implementation of ...
Version 3 is the same as version 2 but only the resulting PDF was uploaded, to avoid this bug: http:...
Monte Carlo methods provide approximate numerical solutions to problems that would be difficult or i...
We provide a review of the state of the art on the design and implementation of random number genera...
International audienceStochastic simulations are often sensitive to the source of randomness that ch...
International audienceStochastic simulations are often sensitive to the randomness source that chara...
International audienceParallel stochastic simulations tend to exploit more and more computing power ...
The race to computing power increases every day in the simulation community. A few years ago, scient...
International audienceRandom number generation is a key element of stochastic simulations. It has be...
Monte Carlo methods rely on sequences of random numbers to obtain solutions to many problems in scie...
This work considers the deployment of pseudo-random number generators (PRNGs) on graphics processing...
The future of high-performance computing is aligning itself towards the efficient use of highly para...
Abstract EFFICIENT RANDOM NUMBER GENERATION FOR FERMI CLASS GPUs by NIRODHA ABEYWARDANA JAN 2012 Adv...
International audienceRandom number generation is a key element of stochastic simulations. It has be...
Monte Carlo methods rely on sequences of random numbers to obtain solutions to many problems in scie...
High-performance streams of (pseudo) random numbers are crucial for the efficient implementation of ...
Version 3 is the same as version 2 but only the resulting PDF was uploaded, to avoid this bug: http:...
Monte Carlo methods provide approximate numerical solutions to problems that would be difficult or i...
We provide a review of the state of the art on the design and implementation of random number genera...