Efficient pseudo-random number generators for biomolecular simulations on graphics processors

Details Efficient pseudo-random number generators for biomolecular simulations on graphics processors Efficient pseudo-random number generators for biomolecular simulations on graphics processors

2010-03-04

arxiv.org/abs/1003.1123v1

Physics

Chemical Physics

32 pages, 6 figures, 2 tables

Scientific paper

Langevin Dynamics, Monte Carlo, and all-atom Molecular Dynamics simulations in implicit solvent, widely used to access the microscopic transitions in biomolecules, require a reliable source of random numbers. Here we present the two main approaches for implementation of random number generators (RNGs) on a GPU, which enable one to generate random numbers on the fly. In the one-RNG-per-thread approach, inherent in CPU-based calculations, one RNG produces a stream of random numbers in each thread of execution, whereas the one-RNG-for-all-threads approach builds on the ability of different threads to communicate, thus, sharing random seeds across the entire GPU device. We exemplify the use of these approaches through the development of Ran2, Hybrid Taus, and Lagged Fibonacci algorithms fully implemented on the GPU. As an application-based test of randomness, we carry out LD simulations of N independent harmonic oscillators coupled to a stochastic thermostat. This model allows us to assess statistical quality of random numbers by comparing the simulation output with the exact results that would be obtained with truly random numbers. We also profile the performance of these generators in terms of the computational time, memory usage, and the speedup factor (CPU/GPU time).

Affiliated with

Also associated with

No associations

Rating

Efficient pseudo-random number generators for biomolecular simulations on graphics processors does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Efficient pseudo-random number generators for biomolecular simulations on graphics processors, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Efficient pseudo-random number generators for biomolecular simulations on graphics processors will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-686657