From brianh@scg.scg.fujitsu.com Wed Mar 15 13:16:05 1995 Received: from mail.barrnet.net for brianh@scg.scg.fujitsu.com by www.ccl.net (8.6.10/930601.1506) id NAA01990; Wed, 15 Mar 1995 13:10:06 -0500 Received: from fujitsu1.fujitsu.com by mail.barrnet.net (8.6.10/BARRNET-Len-Rose) id KAA13598; Wed, 15 Mar 1995 10:10:05 -0800 Received: from scg.scg.fai.com (scg.scg.fujitsu.com) by fujitsu1.fujitsu.com (4.1/SMI-4.1) id AA16519; Wed, 15 Mar 95 10:10:41 PST Received: by scg.scg.fai.com (4.1/SMI-4.1) id AA16432; Wed, 15 Mar 95 10:11:51 PST Date: Wed, 15 Mar 95 10:11:51 PST From: brianh@scg.scg.fujitsu.com (Brian Hammond) Message-Id: <9503151811.AA16432@scg.scg.fai.com> To: chemistry@ccl.net Subject: Random number generator for QMC Cc: brianh@scg.scg.fujitsu.com Dave Young writes: >Hello, > > I am starting to do Quantum Monte Carlo calculations and >I am interested in the performance of random number generators. > > There have been a number of tests developed, the most trusted >seem to be those in "Seminumerical Algorithms" by Knuth. And there >are a number of supplemental random number generators, such as the >ran3 generator in "Numerical Recipies". It has also been demonstrated >that in the past the random number generators built into various >programming languages were not to be trusted. > > My question is - Do the random number generators built into >the current generation of compilers pass statistical tests? > > I have tested the built in random number generators in >Borland C++ and GNU C++ and so far they have passed all tests >(working out of Knuth). I would like to know if it is only C++ that >has a reliable random number generator implemented or if all >compilers are now reliable, or if it is only certain vendors even within >the C++ language? > > The reason that I would like to use built in random number >generators is that Knuth indicates that code written directly in >assembly language can accomplish the task faster than code written in >standard source code. The GNU C++ built in random number generator >is a factor of 2 faster than the ran3 generator using all available >compiler optimization. > > > Dave Young > young@slater.cem.msu.edu > youngdc@msucem > For QMC calculations the "quality" of pseudo-random numbers depends on the algorithm used. Most modern Fortran- or C-library pseudo-random number generators are good enough, particularly if you are doing branching in which you are using a random number of pseudo-random numbers. Also you must consider how to create Gaussian distributed random numbers if your algorithm calls for them. I have seen presentations where the overall cycle length of the underlying pseudo-random number generator is quite noticeable due to creating Gaussian numbers by adding 12 uniformly distributed numbers. So, in general use a pseudo-random number generator with a long cycle length and use Box-Muller if you want Gaussian pseudo-random numbers. -Brian ======================================================================== Brian L. Hammond _/_/_/_/ _/_/_/ _/_/_/_/_/ Computational Research Div. _/ _/ _/ _/ Fujitsu America, Inc. _/_/_/ _/_/_/_/_/ _/ 3055 Orchard Drive _/ _/ _/ _/ San Jose, CA 95134 _/ _/ _/ _/_/_/_/_/ Tel: (408) 456-7322 Email: brianh@fai.com