Computational Science Technical Note CSTN-122

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Performance and Quality of Random Number Generators

V. Du Preez, M. G. B. Johnson, A. Leist and K. A. Hawick

Archived January 2011

Abstract

Random number generation continues to be a critical component in much of computational science and the tradeoff between quality and computational performance is a key issue for many numerical simulations. We review the performance and statistical quality of some well known algorithms for generating pseudo random numbers. Graphical Processing Units (GPUs) are a powerful platform for accelerating computational performance of simulations and random numbers can be generated directly within GPU code or from hosting CPU code. We consider an alternative approach using high quality and genuinely ``random'' deviates generated using a Quantum device and we report on how such a PCI bus device can be linked to a CPU program. We discuss computational performance and statistical quality tradeoffs of this architectural model for Monte Carlo simulations such as the Ising system.

Keywords: quantum random number generation; GPU; CUDA.

Full Document Text: PDF version.

Citation Information: BiBTeX database for CSTN Notes.

BiBTeX reference:

@INPROCEEDINGS{CSTN-122,
  author = {V. Du Preez and M. G. B.Johnson and A. Leist and K. A. Hawick},
  title = {Performance and Quality of Random Number Generators},
  booktitle = {International Conference on Foundations of Computer Science (FCS'11)},
  year = {2011},
  number = {FCS4818},
  pages = {16-21},
  address = {Las Vegas, USA},
  month = {18-21 July},
  publisher = {CSREA},
  t


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