G05KHF (PDF version)
G05 Chapter Contents
G05 Chapter Introduction
NAG Library Manual

NAG Library Routine Document


Note:  before using this routine, please read the Users' Note for your implementation to check the interpretation of bold italicised terms and other implementation-dependent details.


    1  Purpose
    7  Accuracy

1  Purpose

G05KHF allows for the generation of multiple, independent, sequences of pseudorandom numbers using the leap-frog method.

2  Specification


3  Description

G05KHF adjusts a base generator to allow multiple, independent, sequences of pseudorandom numbers to be generated via the leap-frog method (see the G05 Chapter Introduction for details).
If, prior to calling G05KHF the base generator defined by STATE would produce random numbers x1 , x2 , x3 , , then after calling G05KHF the generator will produce random numbers xk , xk+n , xk+2n , xk+3n , .
One of the initialization routines G05KFF (for a repeatable sequence if computed sequentially) or G05KGF (for a non-repeatable sequence) must be called prior to the first call to G05KHF.
The leap-frog algorithm can be used in conjunction with the NAG basic generator, both the Wichmann–Hill I and Wichmann–Hill II generators, the Mersenne Twister and L'Ecuyer.

4  References

Knuth D E (1981) The Art of Computer Programming (Volume 2) (2nd Edition) Addison–Wesley

5  Parameters

1:     N – INTEGERInput
On entry: n, the total number of sequences required.
Constraint: N>0.
2:     K – INTEGERInput
On entry: k, the number of the current sequence.
Constraint: 0<KN.
3:     STATE* – INTEGER arrayCommunication Array
Note: the actual argument supplied must be the array STATE supplied to the initialization routines G05KFF or G05KGF.
On entry: contains information on the selected base generator and its current state.
On exit: contains updated information on the state of the generator.
4:     IFAIL – INTEGERInput/Output
On entry: IFAIL must be set to 0, -1​ or ​1. If you are unfamiliar with this parameter you should refer to Section 3.3 in the Essential Introduction for details.
For environments where it might be inappropriate to halt program execution when an error is detected, the value -1​ or ​1 is recommended. If the output of error messages is undesirable, then the value 1 is recommended. Otherwise, if you are not familiar with this parameter, the recommended value is 0. When the value -1​ or ​1 is used it is essential to test the value of IFAIL on exit.
On exit: IFAIL=0 unless the routine detects an error or a warning has been flagged (see Section 6).

6  Error Indicators and Warnings

If on entry IFAIL=0 or -1, explanatory error messages are output on the current error message unit (as defined by X04AAF).
Errors or warnings detected by the routine:
On entry, N=value.
Constraint: N1.
On entry, K=value and N=value.
Constraint: 0<KN.
On entry, STATE vector has been corrupted or not initialized.
On entry, cannot use leap-frog with the base generator defined by STATE.
An unexpected error has been triggered by this routine. Please contact NAG.
See Section 3.8 in the Essential Introduction for further information.
Your licence key may have expired or may not have been installed correctly.
See Section 3.7 in the Essential Introduction for further information.
Dynamic memory allocation failed.
See Section 3.6 in the Essential Introduction for further information.

7  Accuracy

Not applicable.

8  Parallelism and Performance

Not applicable.

9  Further Comments

The leap-frog method tends to be less efficient than other methods of producing multiple, independent sequences. See the G05 Chapter Introduction for alternative choices.

10  Example

This example creates three independent sequences using G05KHF, after initialization by G05KFF. Five variates from a uniform distribution are then generated from each sequence using G05SAF.

10.1  Program Text

Program Text (g05khfe.f90)

10.2  Program Data

Program Data (g05khfe.d)

10.3  Program Results

Program Results (g05khfe.r)

G05KHF (PDF version)
G05 Chapter Contents
G05 Chapter Introduction
NAG Library Manual

© The Numerical Algorithms Group Ltd, Oxford, UK. 2015