Evidence map›Paper›PMID 38782852›Full record

ArticleNano convergence2024

Demonstration of an energy-efficient Ising solver composed of Ovonic threshold switch (OTS)-based nano-oscillators (OTSNOs).

Young Woong Lee, Seon Jeong Kim, Jaewook Kim, Sangheon Kim, Jongkil Park, YeonJoo Jeong, Gyu Weon Hwang, Seongsik Park, Bae Ho Park, Suyoun Lee

Abstract read
In one paragraph

Article in Nano convergence, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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0cells of the map it votes in
2citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Young Woong LeeCenter for Neuromorphic Engineering, Korea Institute of Science and Technology, Seoul, 02792, Korea.
Seon Jeong KimCenter for Neuromorphic Engineering, Korea Institute of Science and Technology, Seoul, 02792, Korea.
Jaewook KimCenter for Neuromorphic Engineering, Korea Institute of Science and Technology, Seoul, 02792, Korea.
Sangheon KimCenter for Neuromorphic Engineering, Korea Institute of Science and Technology, Seoul, 02792, Korea.
Jongkil ParkCenter for Neuromorphic Engineering, Korea Institute of Science and Technology, Seoul, 02792, Korea.
YeonJoo JeongCenter for Neuromorphic Engineering, Korea Institute of Science and Technology, Seoul, 02792, Korea.
Gyu Weon HwangCenter for Neuromorphic Engineering, Korea Institute of Science and Technology, Seoul, 02792, Korea.
Seongsik ParkCenter for Neuromorphic Engineering, Korea Institute of Science and Technology, Seoul, 02792, Korea.
Bae Ho ParkDepartment of Physics, Division of Quantum Phases & Devices, Konkuk University, Seoul, 05029, Korea.
Suyoun LeeCenter for Neuromorphic Engineering, Korea Institute of Science and Technology, Seoul, 02792, Korea.ORCID http://orcid.org/0000-0002-5147-6821

Funding

Korea Basic Science Institute 2022R1A6C101A754Korea Institute of Science and Technology 2E32960National Research Foundation (KR) 2022R1A2C3004135National Research Foundation (KR) NRF-2021M3F3A2A01037814National Research Foundation (KR) NRF-2021M3F3A2A03017782
6 · The paper itself

Abstract

As there is an increasing need for an efficient solver of combinatorial optimization problems, much interest is paid to the Ising machine, which is a novel physics-driven computing system composed of coupled oscillators mimicking the dynamics of the system of coupled electronic spins. In this work, we propose an energy-efficient nano-oscillator, called OTSNO, which is composed of an Ovonic Threshold Switch (OTS) and an electrical resistor. We demonstrate that the OTSNO shows the synchronization behavior, an essential property for the realization of an Ising machine. Furthermore, we have discovered that the capacitive coupling is advantageous over the resistive coupling for the hardware implementation of an Ising solver by providing a larger margin of the variations of components. Finally, we implement an Ising machine composed of capacitively-coupled OTSNOs to demonstrate that the solution to a 14-node MaxCut problem can be obtained in 40 µs while consuming no more than 2.3 µJ of energy. Compared to a previous hardware implementation of the phase-transition nano-oscillator (PTNO)-based Ising machine, the OTSNO-based Ising machine in this work shows the performance of the increased speed by more than one order while consuming less energy by about an order.

Indexed as

Ising solverOscillator-based computingOvonic threshold switch (OTS)

Identifiers

PMID38782852
PMCPMC11116306

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.