Parallel random number generators for sequences uniformly distributed over any range of integers

Author(s):  
R. Kuehnel ◽  
J. Theiler ◽  
Yuke Wang
1996 ◽  
Vol 07 (02) ◽  
pp. 181-190 ◽  
Author(s):  
MOSHE SIPPER ◽  
MARCO TOMASSINI

Random numbers are needed in a variety of applications, yet finding good random number generators is a difficult task. In this paper non-uniform cellular automata (CA) are studied, presenting the cellular programming algorithm for co-evolving such CAs to perform computations. The algorithm is applied to the evolution of random number generators; our results suggest that evolved generators are at least as good as previously described CAs, with notable advantages arising from the existence of a "tunable" algorithm for obtaining random number generators.


2019 ◽  
Vol 75 (7) ◽  
pp. 3866-3881
Author(s):  
Tadej Ciglarič ◽  
Rok Češnovar ◽  
Erik Štrumbelj

VLSI Design ◽  
2010 ◽  
Vol 2010 ◽  
pp. 1-11 ◽  
Author(s):  
JunKyu Lee ◽  
Gregory D. Peterson ◽  
Robert J. Harrison ◽  
Robert J. Hinde

The Scalable Parallel Random Number Generators (SPRNGs) library is widely used in computational science applications such as Monte Carlo simulations since SPRNG supports fast, parallel, and scalable random number generation with good statistical properties. In order to accelerate SPRNG, we develop a Hardware-Accelerated version of SPRNG (HASPRNG) on the Xilinx XC2VP50 Field Programmable Gate Arrays (FPGAs) in the Cray XD1 that produces identical results. HASPRNG includes the reconfigurable logic for FPGAs along with a programming interface which performs integer random number generation. To demonstrate HASPRNG for Reconfigurable Computing (RC) applications, we also develop a Monte Carlo π-estimator for the Cray XD1. The RC Monte Carlo π-estimator shows a 19.1× speedup over the 2.2 GHz AMD Opteron processor in the Cray XD1. In this paper we describe the FPGA implementation for HASPRNG and a π-estimator example application exploiting the fine-grained parallelism and mathematical properties of the SPRNG algorithm.


2009 ◽  
Vol 180 (12) ◽  
pp. 2574-2581 ◽  
Author(s):  
JunKyu Lee ◽  
Yu Bi ◽  
Gregory D. Peterson ◽  
Robert J. Hinde ◽  
Robert J. Harrison

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