A Pseudo-random Number Generator for Multi-Sequence Generation with Programmable Statistics
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arXiv
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| Auteurs principaux: | , , , , |
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| Format: | Preprint |
| Publié: |
2024
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| _version_ | 1866915086780596224 |
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| author | Wu, Jianan Salim, Ahmet Yusuf Elmitwalli, Eslam Köse, Selçuk Ignjatovic, Zeljko |
| author_facet | Wu, Jianan Salim, Ahmet Yusuf Elmitwalli, Eslam Köse, Selçuk Ignjatovic, Zeljko |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2501_00193 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | A Pseudo-random Number Generator for Multi-Sequence Generation with Programmable Statistics Wu, Jianan Salim, Ahmet Yusuf Elmitwalli, Eslam Köse, Selçuk Ignjatovic, Zeljko Cryptography and Security Information Theory 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. |
| title | A Pseudo-random Number Generator for Multi-Sequence Generation with Programmable Statistics |
| topic | Cryptography and Security Information Theory |
| url | https://arxiv.org/abs/2501.00193 |