Probabilistic computing enabled by continuous random numbers sampled from in-plane magnetized stochastic magnetic tunnel junctions

Hardware acceleration of probabilistic computing has recently attracted significant attention in the slowing down of Moore's law. A randomly fluctuating bit called as p-bit constitutes a fundamental building block for this type of physics-inspired computing scheme, which can be efficiently built out of emerging devices. Here, we report a probabilistic computing set-up, where random numbers are sampled from stochastic magnetic tunnel junctions with in-plane magnetic anisotropy. Although the sampled data have largely bipolar-like probability distributions compared to the ideally uniform ones, the results show a reasonable performance in a standard simulated annealing process on Boolean satisfiability problems up to 100 variables. The systematic simulations suggest the importance of probability distribution where some additional intermediate states help to increase the performance.

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Publication Details

Journal
Applied Physics Letters
Published
2024-09-30
DOI
https://doi.org/10.1063/5.0223479
Citations
3
Primary Topic
Quantum Computing Algorithms and Architecture
Type
article
Field-Weighted Citation Impact
1.04

Funders

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article

Probabilistic computing enabled by continuous random numbers sampled from in-plane magnetized stochastic magnetic tunnel junctions

Ki-Hyuk Han, YongJin Kim, Hyun Cheol Koo, OukJae Lee et al.
3 citations
Applied Physics Letters
Quantum Computing Algorithms and Architecture
1.04
article

Probabilistic computing enabled by continuous random numbers sampled from in-plane magnetized stochastic magnetic tunnel junctions

Ki-Hyuk Han, YongJin Kim, Hyun Cheol Koo, OukJae Lee, Seokmin Hong
article en
3 citations

Abstract

Hardware acceleration of probabilistic computing has recently attracted significant attention in the slowing down of Moore's law. A randomly fluctuating bit called as p-bit constitutes a fundamental building block for this type of physics-inspired computing scheme, which can be efficiently built out of emerging devices. Here, we report a probabilistic computing set-up, where random numbers are sampled from stochastic magnetic tunnel junctions with in-plane magnetic anisotropy. Although the sampled data have largely bipolar-like probability distributions compared to the ideally uniform ones, the results show a reasonable performance in a standard simulated annealing process on Boolean satisfiability problems up to 100 variables. The systematic simulations suggest the importance of probability distribution where some additional intermediate states help to increase the performance.

Applied Physics LettersVol. 125(14)
Korea University (KR), Korea Institute of Science and Technology (KR)
Korea Institute of Science and Technology
Openalex Percentile: Top 19%
Quantum Computing Algorithms and Architecture
1.04
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