Intel® High Level Synthesis Compiler Pro Edition: Reference Manual

ID 683349
Date 3/28/2022

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A.1. Random Number Generator Library

The random number generator source code library provided with the Intel® HLS Compiler Pro Edition gives you FPGA-optimized random number generator template classes that you can add to your component without needing to write your own.

The Random Number Generator Library and Cryptography

The use of these pseudo-random number generator (PRNG) algorithms are not recommended for cryptographic purposes. The PRNGs included in this library are not cryptographically-secure pseudo-random number generators (CSPRNGs) and should not be used for cryptography. CSPRNG algorithms are designed so that no polynomial-time algorithm (PTA) can compute or predict the next bit in the pseudo-random sequence, nor is there a PTA that can predict past values of the CSPRNG; these algorithms do not achieve this purpose. Additionally, these algorithms have not been reviewed nor are they recommended for use as a PRNG component of a CSPRNG, even if the input values are from a non-deterministic entropy source with an appropriate entropy extractor.

Table 61.  Properties of Values That Can Be Generated by the Intel® HLS Compiler Random Number Generator Library
Value distribution Value type Value range Generation method
Uniform Integer [-2³¹, 2³¹-1] Tausworthe Generator
Floating point [0, 1) (non-inclusive) Tausworthe Generator
Gaussian Floating point [0, 1) Central limit theorem (CLT) (Default)

Header File

To include the random number generator library in your component, add the following line to your component:
#include "HLS/rand_lib.h"

The header file is self-documented. You can review the header file to learn how to use the random number generator library in your component.

Random Number Object Declarations

Declare random number objects in your components as follows. In all cases, specifying <seed_value> is optional.
  • Uniform distribution integer random number
    static RNG_Uniform<int> <object_name>(<seed_value>)
  • Uniform distribution floating point random number
    static RNG_Uniform<float> <object_name>(<seed_value>)
  • Gaussian distribution floating point random number (CLT method)
    static RNG_Gaussian<float> <object_name>(<seed_value>)
    static RNG_Gaussian<float, ihc::GAUSSIAN_CLT> <object_name>(<seed_value>)
  • Gaussian distribution floating point random number (Box-Muller method)
    static RNG_Gaussian<float, ihc::GAUSSIAN_BOX_MULLER> <object_name>(<seed_value>)

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