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Record W2995856566 · doi:10.1109/tmag.2019.2940581

Energy-Efficient Differential Spin Hall MRAM-Based 4-2 Magnetic Compressor

2019· article· en· W2995856566 on OpenAlexaff
Vikas Nehra, Sanjay Prajapati, Piyush Tankwal, Željko Žilić, T. Nandha Kumar, Brajesh Kumar Kaushik

Bibliographic record

VenueIEEE Transactions on Magnetics · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMagnetic properties of thin films
Canadian institutionsMcGill University
Fundersnot available
KeywordsMagnetoresistive random-access memorySpin-transfer torqueCMOSComputer scienceElectrical engineeringTunnel magnetoresistanceMaterials scienceMagnetizationOptoelectronicsPhysicsMagnetic fieldEngineeringComputer hardwareRandom access memoryNanotechnology

Abstract

fetched live from OpenAlex

The compressors are widely used as bit compressing cells having key applications with multi-operand addition and multiplication hardware. As the CMOS technology scales down below 45 nm technology nodes, static power dissipation becomes a major concern. To overcome this constraint, spin transfer torque magnetic random access memory (STT-MRAM)-based hybrid CMOS/MTJ architectures are being used. Inception of perpendicular magnetic tunnel junction (PMTJ) has enhanced the growth of spintronicsbased hybrid architectures, due to their low switching current, scalability, non-volatility, and CMOS compatibility. Recently, a large number of circuits based on STT-MRAM have been proposed. However, they have limitations related to reliability and high write energy. In this article, we propose a differential spin Hall MRAM (DSH-MRAM)-based hybrid CMOS/MTJ magnetic 4-2 compressor. A write voltage of 0.4 V and 300 ps current pulse are used to switch the magnetization state of the MTJs. When compared with previous STT-MRAM-based designs, the proposed compressor shows 97% improvement in power-delay product (PDP) characteristics. The write circuit in DSH-MRAM consumes merely 5 nW in comparison to 2 μW by conventional STT-MRAM designs. Moreover, the narrow write pulse promotes the proposed design for input frequencies up to 1 GHz.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.693
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0250.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.008
GPT teacher head0.206
Teacher spread0.198 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations13
Published2019
Admission routes1
Has abstractyes

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