Chapter Notes

  Knuth [175] provides a wealth of material on random number generation, including a table of appropriate values for a and m and tests that can be used to determine the quality of a particular generator. See in particular the table on page 102. Anderson [13] provides a more up-to-date survey of random number generation algorithms. He includes a short but useful section on parallel computers and provides numerous references. The random tree method was first described by Frederickson et al. [114].

Random numbers are used extensively in the Monte Carlo method, in which a large, statistically valid sequence of ``samples'' is used to compute properties of mathematical functions or physical processes.   Koonin [177] provides a good introduction to the computational   issues associated with Monte Carlo methods on sequential computers, and Kalos [163] provides a more detailed discussion.

Here is a Web Tour providing access to additional information on random number generation on parallel computers.