Probabilistic computing with NbOx metal-insulator transition-based self-oscillatory pbit
Abstract Energy-based computing is a promising approach for addressing the rising demand for solving NP-hard problems across diverse domains, including logistics, artificial intelligence, cryptography, and optimization. Probabilistic computing utilizing pbits, which can be manufactured using the sem...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2023-11-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-023-43085-6 |
| _version_ | 1797630082624258048 |
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| author | Hakseung Rhee Gwangmin Kim Hanchan Song Woojoon Park Do Hoon Kim Jae Hyun In Younghyun Lee Kyung Min Kim |
| author_facet | Hakseung Rhee Gwangmin Kim Hanchan Song Woojoon Park Do Hoon Kim Jae Hyun In Younghyun Lee Kyung Min Kim |
| author_sort | Hakseung Rhee |
| collection | DOAJ |
| description | Abstract Energy-based computing is a promising approach for addressing the rising demand for solving NP-hard problems across diverse domains, including logistics, artificial intelligence, cryptography, and optimization. Probabilistic computing utilizing pbits, which can be manufactured using the semiconductor process and seamlessly integrated with conventional processing units, stands out as an efficient candidate to meet these demands. Here, we propose a novel pbit unit using an NbO x volatile memristor-based oscillator capable of generating probabilistic bits in a self-clocking manner. The noise-induced metal-insulator transition causes the probabilistic behavior, which can be effectively modeled using a multi-noise-induced stochastic process around the metal-insulator transition temperature. We demonstrate a memristive Boltzmann machine based on our proposed pbit and validate its feasibility by solving NP-hard problems. Furthermore, we propose a streamlined operation methodology that considers the autocorrelation of individual bits, enabling energy-efficient and high-performance probabilistic computing. |
| first_indexed | 2024-03-11T11:02:56Z |
| format | Article |
| id | doaj.art-19794d761d3249acbc607533a35f8edc |
| institution | Directory Open Access Journal |
| issn | 2041-1723 |
| language | English |
| last_indexed | 2024-03-11T11:02:56Z |
| publishDate | 2023-11-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Nature Communications |
| spelling | doaj.art-19794d761d3249acbc607533a35f8edc2023-11-12T12:23:02ZengNature PortfolioNature Communications2041-17232023-11-011411810.1038/s41467-023-43085-6Probabilistic computing with NbOx metal-insulator transition-based self-oscillatory pbitHakseung Rhee0Gwangmin Kim1Hanchan Song2Woojoon Park3Do Hoon Kim4Jae Hyun In5Younghyun Lee6Kyung Min Kim7Department of Materials Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST)Department of Materials Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST)Department of Materials Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST)Department of Materials Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST)Department of Materials Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST)Department of Materials Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST)Department of Materials Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST)Department of Materials Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST)Abstract Energy-based computing is a promising approach for addressing the rising demand for solving NP-hard problems across diverse domains, including logistics, artificial intelligence, cryptography, and optimization. Probabilistic computing utilizing pbits, which can be manufactured using the semiconductor process and seamlessly integrated with conventional processing units, stands out as an efficient candidate to meet these demands. Here, we propose a novel pbit unit using an NbO x volatile memristor-based oscillator capable of generating probabilistic bits in a self-clocking manner. The noise-induced metal-insulator transition causes the probabilistic behavior, which can be effectively modeled using a multi-noise-induced stochastic process around the metal-insulator transition temperature. We demonstrate a memristive Boltzmann machine based on our proposed pbit and validate its feasibility by solving NP-hard problems. Furthermore, we propose a streamlined operation methodology that considers the autocorrelation of individual bits, enabling energy-efficient and high-performance probabilistic computing.https://doi.org/10.1038/s41467-023-43085-6 |
| spellingShingle | Hakseung Rhee Gwangmin Kim Hanchan Song Woojoon Park Do Hoon Kim Jae Hyun In Younghyun Lee Kyung Min Kim Probabilistic computing with NbOx metal-insulator transition-based self-oscillatory pbit Nature Communications |
| title | Probabilistic computing with NbOx metal-insulator transition-based self-oscillatory pbit |
| title_full | Probabilistic computing with NbOx metal-insulator transition-based self-oscillatory pbit |
| title_fullStr | Probabilistic computing with NbOx metal-insulator transition-based self-oscillatory pbit |
| title_full_unstemmed | Probabilistic computing with NbOx metal-insulator transition-based self-oscillatory pbit |
| title_short | Probabilistic computing with NbOx metal-insulator transition-based self-oscillatory pbit |
| title_sort | probabilistic computing with nbox metal insulator transition based self oscillatory pbit |
| url | https://doi.org/10.1038/s41467-023-43085-6 |
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