A fast normal random number generator
ACM Transactions on Mathematical Software (TOMS)
Development of a mathematical subroutine library for Fujitsu vector parallel processors
ICS '98 Proceedings of the 12th international conference on Supercomputing
A Hardware Gaussian Noise Generator Using the Box-Muller Method and Its Error Analysis
IEEE Transactions on Computers
Gaussian random number generators
ACM Computing Surveys (CSUR)
A compact and accurate Gaussian variate generator
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Proceedings of the ACM/SIGDA international symposium on Field programmable gate arrays
An Optimized Hardware Architecture of a Multivariate Gaussian Random Number Generator
ACM Transactions on Reconfigurable Technology and Systems (TRETS)
A hardware gaussian noise generator using the wallace method
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Fast and reliable random number generators for scientific computing
PARA'04 Proceedings of the 7th international conference on Applied Parallel Computing: state of the Art in Scientific Computing
A configuration deactivation algorithm for boosting probabilistic roadmap planning of robots
International Journal of Automation and Computing
A hardware efficient random number generator for nonuniform distributions with arbitrary precision
International Journal of Reconfigurable Computing - Special issue on Selected Papers from the International Conference on Reconfigurable Computing and FPGAs (ReConFig'10)
FPGA acceleration using high-level languages of a Monte-Carlo method for pricing complex options
Journal of Systems Architecture: the EUROMICRO Journal
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Fast algorithms for generating pseudorandom numbers from the unit-normal and unit-exponential distributions are described. The methods are unusual in that they do not rely on a source of uniform random numbers, but generate the target distributions directly by using their maximal-entropy properties. The algorithms are fast. The normal generator is faster than the commonly used Unix library uniform generator “random” when the latter is used to yield real values. Their statistical properties seem satisfactory, but only a limited suite of tests has been conducted. They are written in C and as written assume 32-bit integer arithmetic. The code is publicly available as C source and can easily be adopted for longer word lengths and/or vector processing.