Evidence map›Paper›PMID 42221053›Full record

ArticlePhysical review applied2020

Distance Computation Based on Coupled Spin-Torque Oscillators: Application to Image Processing.

Minsuk Koo, M R Pufall, Yong Shim, A B Kos, Gyorgy Csaba, Wolfgang Porod, W H Rippard, Kaushik Roy

Abstract read
In one paragraph

Article in Physical review applied, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Minsuk KooDepartment of Computer Science and Engineering, Incheon National University, Incheon, South Korea.ORCID 0000-0003-2522-6754
M R PufallQuantum Electromagnetics Division, National Institute of Standards and Technology, 325 Broadway, Boulder, Colorado 80305, USA.
Yong ShimSchool of Electrical and Electronics Engineering, Chung-Ang University, Seoul, South Korea.
A B KosQuantum Electromagnetics Division, National Institute of Standards and Technology, 325 Broadway, Boulder, Colorado 80305, USA.
Gyorgy CsabaFaculty of Technology and Bionics, Pazmany Peter Catholic University, Budapest, Hungary.ORCID 0000-0001-7592-0256
Wolfgang PorodCenter for Nano Science and Technology, University of Notre Dame, Notre Dame, Indiana 46556, USA.
W H RippardQuantum Electromagnetics Division, National Institute of Standards and Technology, 325 Broadway, Boulder, Colorado 80305, USA.
Kaushik RoyDepartment of Electrical and Computer Engineering, Purdue University, West Lafayette, Indiana 47907, USA.

Funding

Intramural NIST DOC 9999-NIST
6 · The paper itself

Abstract

Recent research on nano-oscillators has shown the possibility of using a coupled-oscillator network as a core-computing primitive for non-Boolean computation. The spin-torque oscillator (STO) is an attractive candidate because it is CMOS compatible, highly integrable, scalable, and frequency and phase tunable. Based on these promising features, we propose an alternative coupled-oscillator-based architecture for hybrid spintronic and CMOS hardware that computes a multidimensional norm. The hybrid system, composed of an array of four injection-locked STOs and a CMOS detector, is experimentally demonstrated. The measured performance is then used as the input to simulations that demonstrate the hybrid system as both a distance metric and a convolution computational primitive for image-processing applications. Energy and scaling analysis shows that the STO-based coupled-oscillatory system has a higher efficiency than the CMOS-based system with an order of magnitude faster computation speed in distance computation for high-dimensional input vectors.

Identifiers

PMID42221053
PMCPMC13218320

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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.