A Pseudo-random Number Generator for Multi-Sequence Generation with Programmable Statistics

Pseudo-random number generators (PRNGs) are essential in a wide range of applications, from cryptography to statistical simulations and optimization algorithms. While uniform randomness is crucial for security-critical areas like cryptography, many domains, such as simulated annealing and CMOS-based Ising Machines, benefit from controlled or nonuniform randomness to enhance solution exploration and optimize performance. This paper presents a hardware PRNG that can simultaneously generate multiple uncorrelated sequences with programmable statistics tailored to specific application needs. Designed in 65nm process, the PRNG occupies an area of approximately 0.0013mm<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> and has an energy consumption of 0.57pJ/bit. Simulations confirm the PRNG's effectiveness in modulating the statistical distribution while demonstrating high-quality randomness properties.

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Published
2025-05-25
DOI
https://doi.org/10.1109/iscas56072.2025.11044009
Primary Topic
Algorithms and Data Compression
Type
article
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article

A Pseudo-random Number Generator for Multi-Sequence Generation with Programmable Statistics

Zeljko Ignjatovic, Eslam Elmitwalli, Jianan Wu, Selçuk Köse et al.
Algorithms and Data Compression
article

A Pseudo-random Number Generator for Multi-Sequence Generation with Programmable Statistics

Zeljko Ignjatovic, Eslam Elmitwalli, Jianan Wu, Selçuk Köse, Ahmad Jamal Salim
article en

Abstract

Pseudo-random number generators (PRNGs) are essential in a wide range of applications, from cryptography to statistical simulations and optimization algorithms. While uniform randomness is crucial for security-critical areas like cryptography, many domains, such as simulated annealing and CMOS-based Ising Machines, benefit from controlled or nonuniform randomness to enhance solution exploration and optimize performance. This paper presents a hardware PRNG that can simultaneously generate multiple uncorrelated sequences with programmable statistics tailored to specific application needs. Designed in 65nm process, the PRNG occupies an area of approximately 0.0013mm<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> and has an energy consumption of 0.57pJ/bit. Simulations confirm the PRNG's effectiveness in modulating the statistical distribution while demonstrating high-quality randomness properties.

University of Rochester (US)
Openalex Percentile: Top 93%
Algorithms and Data Compression
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