TY - JOUR
T1 - Random number generators for massively parallel simulations on GPU
AU - Manssen, M.
AU - Weigel, Martin
AU - Hartmann, A. K.
N1 - The full text is not available on the repository.
PY - 2012
Y1 - 2012
N2 - High-performance streams of (pseudo) random numbers are crucial for the efficient implementation of countless stochastic algorithms, most importantly, Monte Carlo simulations and molecular dynamics simulations with stochastic thermostats. A number of implementations of random number generators has been discussed for GPU platforms before and some generators are even included in the CUDA supporting libraries. Nevertheless, not all of these generators are well suited for highly parallel applications where each thread requires its own generator instance. For this specific situation encountered, for instance, in simulations of lattice models, most of the high-quality generators with large states such as Mersenne twister cannot be used efficiently without substantial changes. We provide a broad review of existing CUDA variants of random-number generators and present the CUDA implementation of a new massively parallel high-quality, high-performance generator with a small memory load overhead.
AB - High-performance streams of (pseudo) random numbers are crucial for the efficient implementation of countless stochastic algorithms, most importantly, Monte Carlo simulations and molecular dynamics simulations with stochastic thermostats. A number of implementations of random number generators has been discussed for GPU platforms before and some generators are even included in the CUDA supporting libraries. Nevertheless, not all of these generators are well suited for highly parallel applications where each thread requires its own generator instance. For this specific situation encountered, for instance, in simulations of lattice models, most of the high-quality generators with large states such as Mersenne twister cannot be used efficiently without substantial changes. We provide a broad review of existing CUDA variants of random-number generators and present the CUDA implementation of a new massively parallel high-quality, high-performance generator with a small memory load overhead.
U2 - 10.1140/epjst/e2012-01637-8
DO - 10.1140/epjst/e2012-01637-8
M3 - Article
SN - 1951-6355
SN - 1951-6401
VL - 210
SP - 53
EP - 71
JO - The European Physical Journal Special Topics
JF - The European Physical Journal Special Topics
IS - 1
ER -