Proceedings ArticleDOI
Hardware acceleration of pseudo-random number generation for simulation applications
James M. McCollum,Joseph M. Lancaster,D.W. Bouldin,Gregory D. Peterson +3 more
- pp 299-303
TLDR
The work shows that generating random numbers using the designed hardware can significantly increase the performance of simulation applications that require many random numbers.Abstract:
In modeling and simulation tools, random numbers from a variety of probability distribution functions are generated to simulate the behavior of random events. Inefficient generation of these numbers can be a significant bottleneck for simulation applications. Generating these random numbers imprecisely can skew results. An efficient and scalable fixed-point method for generating random numbers for any probability distribution function in a Field Programmable Gate Array (FPGA) is developed. A Pi estimator, a Monte Carlo integrator, and a stochastic simulator for chemical species are developed in software. Estimates are made regarding their potential to be accelerated using the designed FPGA. Results are presented which examine trade-offs between the number of gates used by the FPGA and the accuracy of the random numbers generated. The work shows that generating random numbers using the designed hardware can significantly increase the performance of simulation applications that require many random numbers.read more
Citations
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Journal ArticleDOI
Gaussian random number generators
TL;DR: The algorithms underlying various GRNGs are described, their computational requirements are compared, and the quality of the random numbers are examined with emphasis on the behaviour in the tail region of the Gaussian probability density function.
Proceedings ArticleDOI
Reconfigurable acceleration for Monte Carlo based financial simulation
Guanglie Zhang,Philip H. W. Leong,C.H. Ho,K.H. Tsoi,C.C.C. Cheung,Dong-U Lee,Ray C. C. Cheung,Wayne Luk +7 more
TL;DR: A novel hardware accelerator for Monte Carlo (MC) simulation, based on a generic architecture, which combines speed and flexibility by integrating a pipelined MC core with an on-chip instruction processor is described.
Proceedings ArticleDOI
Ziggurat-based hardware Gaussian random number generator
TL;DR: An architecture and implementation of a high performance Gaussian random number generator (GRNG) is described and the resulting system can generate 169 million normally distributed random numbers per second on a Xilinx XC2VP3O-6 device.
Journal ArticleDOI
A Compact and Accurate Gaussian Variate Generator
TL;DR: A compact, fast, and accurate realization of a digital Gaussian variate generator (GVG) based on the Box-Muller algorithm is presented, which has a faster Gaussian sample generation rate and higher tail accuracy with a lower hardware cost than published designs.
Journal ArticleDOI
Hardware Generation of Arbitrary Random Number Distributions From Uniform Distributions Via the Inversion Method
TL;DR: An automated methodology for producing hardware-based random number generator designs for arbitrary distributions using the inverse cumulative distribution function (ICDF) with a hierarchical segmentation scheme that involves uniform segments and segments with size varying by powers of two which can adapt to local function nonlinearities.
References
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Journal ArticleDOI
Exact Stochastic Simulation of Coupled Chemical Reactions
TL;DR: In this article, a simulation algorithm for the stochastic formulation of chemical kinetics is proposed, which uses a rigorously derived Monte Carlo procedure to numerically simulate the time evolution of a given chemical system.
Book
The Art of Computer Systems Performance Analysis: Techniques for Experimental Design, Measurement, Simulation, and Modeling
TL;DR: The intended audience and the goals of the book are to provide computer professionals simple and straightforward performance analysis techniques in a comprehensive textbook.
Journal ArticleDOI
Efficient Exact Stochastic Simulation of Chemical Systems with Many Species and Many Channels
Michael A. Gibson,Jehoshua Bruck +1 more
TL;DR: The Next Reaction Method is presented, an exact algorithm to simulate coupled chemical reactions that uses only a single random number per simulation event, and is also efficient.
Book
Application-Specific Integrated Circuits
TL;DR: This book provides the first comprehensive introduction to Application Specific Integrated Circuits (ASICs) with a focus on semi-custom technology.