# Fast pseudorandom generators for normal and exponential variates

@article{Wallace1996FastPG, title={Fast pseudorandom generators for normal and exponential variates}, author={Chris S. Wallace}, journal={ACM Trans. Math. Softw.}, year={1996}, volume={22}, pages={119-127} }

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…

## 78 Citations

### Random Number Generation and Simulation on Vector and Parallel Computers

- Computer Science, MathematicsEuro-Par
- 1998

This work considers the requirements for a good parallel random number generator, and describes a new class of generators for the normal distribution (based on a proposal by Wallace), which can give very fast vector or parallel implementations.

### Efficient Hardware Generation of Random Variates with Arbitrary Distributions

- Computer Science, Mathematics2006 14th Annual IEEE Symposium on Field-Programmable Custom Computing Machines
- 2006

This paper presents a technique for efficiently generating random numbers from a given probability distribution. This is achieved by using a generic hardware architecture, which transforms uniform…

### A fast vectorised implementation of Wallace's normal random number generator

- Computer Science, MathematicsArXiv
- 2010

A vectorised implementation of Wallace's pseudo-random generators for normal variates RANN4 is described which is more than three times faster than its best competitors (the Polar and Box-Muller methods) on the Fujitsu VP2200 and VPP300.

### A Hardware Efficient Random Number Generator for Nonuniform Distributions with Arbitrary Precision

- Computer ScienceInt. J. Reconfigurable Comput.
- 2012

This paper presents a new design that saves up to 48% of area compared to state-of-the-art inversion-based implementation, usable for arbitrary distributions and precision, and provides a free software tool allowing users to implement their own distributions easily.

### AHardware Efficient RandomNumber Generator for NonuniformDistributions with Arbitrary Precision

- Computer Science
- 2012

This paper presents a new design that saves up to 48% of area compared to state-of-the-art inversion-based implementation, usable for arbitrary distributions and precision, and provides a free software tool allowing users to implement their own distributions easily.

### Fast and Reliable Random Number Generators for Scientific Computing

- Computer SciencePARA
- 2004

The requirements for good uniform random number generators are outlined, and a class of generators having very fast vector/parallel implementations with excellent statistical properties are described.

### Non-standard pseudo random number generators revisited for GPUs

- Computer ScienceFuture Gener. Comput. Syst.
- 2018

### An efficient hardware implementation of Gaussian random number generator

- Computer Science2017 International Conference on Nextgen Electronic Technologies: Silicon to Software (ICNETS2)
- 2017

A pair of 32 bit Gaussian Random Numbers (GRaNs) is generated for the generation of uniform random number skip-ahead linear feedback shift register (SA-LFSR) which is given as input to BM transformation.

### Non-Uniform Random Number Generation Through Piecewise Linear Approximations

- Computer Science2006 International Conference on Field Programmable Logic and Applications
- 2006

Comparisons with Gaussian specific generators show that the new architecture uses less than half the resources, provides a higher sample rate, and retains statistical quality for up to 50 billion samples, but can also generate other distributions.

### VLSI implementation of universal random number generator

- Computer ScienceAsia-Pacific Conference on Circuits and Systems
- 2002

A universal random number generator which can generate random numbers drawn from a uniform distribution, exponential distribution, Rayleigh distribution and Gauss distribution has been implemented as a VLSI circuit, and the simulation and measurement results verify the validity of the design.

## References

SHOWING 1-2 OF 2 REFERENCES

### A fast normal random number generator

- Computer ScienceTOMS
- 1992

A method is presented for generating pseudorandom numbers with a normal distribution using the ratio of uniform deviates method discovered by Kinderman and Monahan with an improved set of bounding curves and can be implemented in 15 lines of FORTRAN.

### TR-CS-93-04

- TR-CS-93-04