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

  • arXiv (Cornell University)
  • Cornell University
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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 non-uniform 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^2 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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Publication details

DOI
10.48550/arxiv.2501.00193
OpenAlex
W4406030940
Document type
preprint
Language
EN
Source
arXiv (Cornell University)
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