Visible to Intel only — GUID: GUID-5C059049-F264-45F9-AC9E-E71A749D5B62
Visible to Intel only — GUID: GUID-5C059049-F264-45F9-AC9E-E71A749D5B62
Distributions
oneMKL RNG routines are used to generate random numbers with different types of distribution. Each function group is introduced below by the type of underlying distribution and contains a short description of its functionality, as well as specifications of the call sequence and the explanation of input and output parameters. The following tables list the random number generator routines with data types and output distributions, and sets correspondence between data types of the generator routines and the basic random number generators.
Type of Distribution |
Data Types |
BRNG Data Type |
Description |
|---|---|---|---|
float, double |
float, double |
Uniform continuous distribution on the interval [a,b) |
|
float, double |
float, double |
Normal (Gaussian) distribution |
|
float, double |
float, double |
Normal (Gaussian) multivariate distribution |
|
float, double |
float, double |
Exponential distribution |
|
float, double |
float, double |
Laplace distribution (double exponential distribution) |
|
float, double |
float, double |
Weibull distribution |
|
float, double |
float, double |
Cauchy distribution |
|
float, double |
float, double |
Rayleigh distribution |
|
float, double |
float, double |
Lognormal distribution |
|
float, double |
float, double |
Gumbel (extreme value) distribution |
|
float, double |
float, double |
Gamma distribution |
|
float, double |
float, double |
Beta distribution |
|
float, double |
float, double |
Chi-Square distribution |
Type of Distribution |
Data Types |
BRNG Data Type |
Description |
|---|---|---|---|
integer |
GPU: float for oneapi::mkl::rng::uniform_method::standard, double for oneapi::mkl::rng::method::accurate CPU: double for both methods |
Uniform discrete distribution on the interval [a,b) |
|
integer |
integer |
Uniformly distributed bits in 32-bit chunks |
|
integer |
integer |
Uniformly distributed bits in 64-bit chunks |
|
integer |
integer |
Bits of underlying BRNG integer sequence |
|
integer |
float |
Bernoulli distribution |
|
integer |
float |
Geometric distribution |
|
integer |
double |
Binomial distribution |
|
integer |
double |
Hypergeometric distribution |
|
integer |
float (for ) oneapi::mkl::rng::poisson_method::gaussian_icdf_based float (for distribution parameter |
Poisson distribution |
|
integer |
double |
Poisson distribution with varying mean |
|
integer |
double |
Negative binomial distribution, or Pascal distribution |
|
integer |
CPU - float GPU - double |
Multinomial distribution |
) and double (for 
) (for oneapi::mkl::rng::poisson_method::ptpe)NOTE: In case of integer check desired distribution for supported data types.
Modes of Random Number Generation
The library provides two modes of random number generation, accurate and fast. Accurate generation mode is intended for the applications that are highly demanding to accuracy of calculations. When used in this mode, the generators produce random numbers lying completely within definitional domain for all values of the distribution parameters. For example, random numbers obtained from the generator of continuous distribution that is uniform on interval [a,b] belong to this interval irrespective of what a and b values may be. Fast mode provides high performance of generation and also guarantees that generated random numbers belong to the definitional domain except for some specific values of distribution parameters. The generation mode is set by specifying relevant value of the method parameter in generator routines. List of distributions that support accurate mode of generation is given in the table below.
Distribution |
Distribution Method |
|---|---|
oneapi::mkl::rng::unform_method::accurate |
|
oneapi::mkl::rng::exponential_method::icdf_accurate |
|
oneapi::mkl::rng::weibull_method::icdf_accurate |
|
oneapi::mkl::rng::rayleigh_method::icdf_accurate |
|
oneapi::mkl::rng::lognormal_method::icdf_accurateoneapi::mkl::rng::lognormal_method::box_muller2_accurate |
|
oneapi::mkl::rng::gamma_method::marsaglia_accurate |
|
oneapi::mkl::rng::beta_method::cja_accurate |