![]() |
CiteULike | ![]() |
CoffeeIV's CiteULike | ![]() |
![]() |
|
![]() |
Register | ![]() |
Log in | ![]() |
Random Number Generators: A Survival Guide for Large Scale Simulationsby: Stephan Mertens
|
Reviews
[Write a review of this article]
Find related articles from these CiteULike users
Find related articles with these CiteULike tags
Posting History
AbstractMonte Carlo simulations are an important tool in statistical physics, complex systems science, and many other fields. An increasing number of these simulations is run on parallel systems ranging from multicore desktop computers to supercomputers with thousands of CPUs. This raises the issue of generating large amounts of random numbers in a parallel application. In this lecture we will learn just enough of the theory of pseudo random number generation to make wise decisions on how to choose and how to use random number generators when it comes to large scale, parallel simulations.
BibTeX record
RIS record