oneMKL RNG Usage Model

A typical algorithm for random number generators is as follows:

1. Create and initialize the object for basic random number generator.

   • Use the skip_ahead or leapfrog function if it is required (used in parallel with random number generation for Host and CPU devices).

2. Create and initialize the object for distribution generator.

3. Call the generate routine to get random numbers with appropriate statistical distribution.

The following example demonstrates generation of random numbers that is output of basic generator (engine) PHILOX4X32X10. The seed is equal to 777. The generator is used to generate 10,000 normally distributed random numbers with parameters a = 5 and sigma= 2. The purpose of the example is to calculate the sample mean for normal distribution with the given parameters.

Example of RNG Usage

Buffer API

#include <iostream>
#include <vector>


#include “CL/sycl.hpp”
#include “mkl_rng_sycl.hpp”


int main() {
    cl::sycl::queue queue;


    const size_t n = 10000;
    std::vector<double> r(n);


    onemkl::rng::philox4x32x10 engine(queue, SEED); // basic random number generator object
    onemkl::rng::gaussian<double, onemkl::rng::box_muller2> distr(5.0, 2.0); //  distribution object


    {
         //create buffer for random numbers
         cl::sycl::buffer<double, 1> r_buf(r.data(), cl::sycl::range<1>{n});


         onemkl::rng::generate(distr, engine, n, r_buf); // perform generation


    }


    double s = 0.0;
    for(int i = 0; i < n; i++) {
        s += r[i];
    }
    s /= n;


    std::cout << “Average = ” << s << std::endl;


    return 0;
}

USM API

#include <iostream>
#include <vector>
#include “CL/sycl.hpp”
#include “mkl_rng_sycl.hpp”


int main() {
  cl::sycl::queue queue;


  const size_t n = 10000;


  // create USM allocator
  cl::sycl::usm_allocator<double, cl::sycl::usm::alloc::shared> allocator(queue.get_context(), queue.get_device());


  // create vector woth USM allocator
  std::vector<double, cl::sycl::usm_allocator<double, cl::sycl::usm::alloc::shared>> r(n, allocator);


  onemkl::rng::philox4x32x10 engine(queue, SEED); // basic random number generator object
  onemkl::rng::gaussian<double, onemkl::rng::box_muller2> distr(5.0, 2.0); // distribution object


  auto event = onemkl::rng::generate(distr, engine, n, r.data()); // perform generation
  // cl::sycl::event object is returned by generate function for synchronisation
  event.wait(); // synchronization can be also done by queue.wait()


  double s = 0.0;
  for(int i = 0; i < n; i++) {
  s += r[i];


  std::cout << “Average = ” << s << std::endl;


  return 0;
}

You can also use USM with raw pointers by using the cl::sycl::malloc_shared function.

Parent topic: Random Number Generators