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Title: Random Number Generation for Petascale Quantum Monte Carlo

Abstract

The quality of random number generators can affect the results of Monte Carlo computations, especially when a large number of random numbers are consumed. Furthermore, correlations present between different random number streams in a parallel computation can further affect the results. The SPRNG software, which the author had developed earlier, has pseudo-random number generators (PRNGs) capable of producing large numbers of streams with large periods. However, they had been empirically tested on only thousand streams earlier. In the work summarized here, we tested the SPRNG generators with over a hundred thousand streams, involving over 10^14 random numbers per test, on some tests. We also tested the popular Mersenne Twister. We believe that these are the largest tests of PRNGs, both in terms of the numbers of streams tested and the number of random numbers tested. We observed defects in some of these generators, including the Mersenne Twister, while a few generators appeared to perform well. We also corrected an error in the implementation of one of the SPRNG generators.

Authors:
Publication Date:
Research Org.:
Florida State Univ., Tallahassee, FL (United States)
Sponsoring Org.:
USDOE Office of Science (SC)
OSTI Identifier:
973573
Report Number(s):
DOE/OR/23338-1
TRN: US201007%%265
DOE Contract Number:  
FG05-08OR23338
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING; DEFECTS; IMPLEMENTATION; RANDOMNESS; COMPUTER CODES; Random number generation, Monte Carlo

Citation Formats

Srinivasan, Ashok. Random Number Generation for Petascale Quantum Monte Carlo. United States: N. p., 2010. Web. doi:10.2172/973573.
Srinivasan, Ashok. Random Number Generation for Petascale Quantum Monte Carlo. United States. https://doi.org/10.2172/973573
Srinivasan, Ashok. 2010. "Random Number Generation for Petascale Quantum Monte Carlo". United States. https://doi.org/10.2172/973573. https://www.osti.gov/servlets/purl/973573.
@article{osti_973573,
title = {Random Number Generation for Petascale Quantum Monte Carlo},
author = {Srinivasan, Ashok},
abstractNote = {The quality of random number generators can affect the results of Monte Carlo computations, especially when a large number of random numbers are consumed. Furthermore, correlations present between different random number streams in a parallel computation can further affect the results. The SPRNG software, which the author had developed earlier, has pseudo-random number generators (PRNGs) capable of producing large numbers of streams with large periods. However, they had been empirically tested on only thousand streams earlier. In the work summarized here, we tested the SPRNG generators with over a hundred thousand streams, involving over 10^14 random numbers per test, on some tests. We also tested the popular Mersenne Twister. We believe that these are the largest tests of PRNGs, both in terms of the numbers of streams tested and the number of random numbers tested. We observed defects in some of these generators, including the Mersenne Twister, while a few generators appeared to perform well. We also corrected an error in the implementation of one of the SPRNG generators.},
doi = {10.2172/973573},
url = {https://www.osti.gov/biblio/973573}, journal = {},
number = ,
volume = ,
place = {United States},
year = {Tue Mar 16 00:00:00 EDT 2010},
month = {Tue Mar 16 00:00:00 EDT 2010}
}