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RandomIterator

Iterator library for lazy calculation and parallel access of counter-based random numbers.

Table of Contents


What is it?

RandomIterator is a small library providing iterators pointing to streams of pseudorandom numbers. The library deploys lazy-evaluation and is intented for usage on multi-thread calculations.

Main features

  1. Five primary generators: Philox, ARS and Threefry from Random123 and Squares3 and Squares4, which are natively implemented.
  2. Completly thread-safe.
  3. Compatibility with all C++ distributions defined in the standard library.
  4. For each seed, the random_iterator::Stream<Distribution, Engine> manages up to
    232{2}^{32}
    streams, with length
    264{2}^{64}
    .
  5. When instantiated to produce 64bit output, like double ou uint64_t, each stream can provide up to 128EB of data.

The Latest Version

Documentation

Reference manual

The complete and updated Doxygen source code documentation in HTML format is available at the Reference documentation web-page. It is also possible to browse the documentation by class, file or name using the links:

1.classes

2.files

3.names

Examples:

#include <random_iterator/Stream.hpp>
#include <random>
#include <iostream>
...

//generator
random_iterator::philox RNG(0x548c9decbce65295);

//std distribution

std::uniform_real_distribution<double>
uniform_dist(0.0, 1.0);

//streams
auto uniform_stream     = random_iterator::make_stream( uniform_dist, RNG, 0);

//using range semantics 
for(auto unf : uniform_stream)
  std::cout << unf << std::endl;

//using subscript operator
for(size_t i=0; i < 100; ++i)
  std::cout << uniform_stream[i] << std::endl;

...

Installation and requirements

RandomIterator iterator is a header-only library with no dependences.

Licensing

RandomIterator is released under the GNU General Public License version 3. Please see the file called LICENSE.

Contacting the developers

Here’s what you should do if you need help or would like to contribute:

  • If you found a bug or what to ask any question, use GitLab issues.
  • If you have an idea, suggestion or whatever, use GitHub issues.
  • If you want to contribute, submit a pull request.

Acknowledgement

The authors acknowledge support by the High Performance and Cloud Computing Group at the Zentrum für Datenverarbeitung of the University of Tübingen, the state of Baden- Württemberg through bwHPC and the German Research Foundation (DFG) through grant no. INST 37/935-1 FUGG.