Evidence map›Paper›PMID 39791768›Full record

ArticleNanomaterials (Basel, Switzerland)2024

Cryo-SIMPLY: A Reliable STT-MRAM-Based Smart Material Implication Architecture for In-Memory Computing.

Tatiana Moposita, Esteban Garzón, Adam Teman, Marco Lanuzza

Abstract read
In one paragraph

Article in Nanomaterials (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Tatiana MopositaDepartment of Computer Engineering, Modeling, Electronics, and Systems Engineering, University of Calabria, 87036 Rende, Italy.ORCID 0000-0002-7543-4810
Esteban GarzónDepartment of Computer Engineering, Modeling, Electronics, and Systems Engineering, University of Calabria, 87036 Rende, Italy.ORCID 0000-0002-5862-2246
Adam TemanEmerging NanoScaled Integrated Circuits & Systems Labs, Faculty of Engineering, Bar-Ilan University, Ramat Gan 5290002, Israel.ORCID 0000-0002-8233-4711
Marco LanuzzaDepartment of Computer Engineering, Modeling, Electronics, and Systems Engineering, University of Calabria, 87036 Rende, Italy.ORCID 0000-0002-6480-9218

Funding

the Italian Ministry of University and Research (MUR) PRIN 2020LWPKH7the Lise Meitner Grants for Israeli-Swedish Research Collaboration AutoPiM
6 · The paper itself

Abstract

This paper presents Cryo-SIMPLY, a reliable smart material implication (SIMPLY) operating at cryogenic conditions (77 K). The assessment considers SIMPLY schemes based on spin-transfer torque magnetic random access memory (STT-MRAM) technology with single-barrier magnetic tunnel junction (SMTJ) and double-barrier magnetic tunnel junction (DMTJ). Our study relies on a temperature-aware macrospin-based Verilog-A compact model for MTJ devices and a 65 nm commercial process design kit (PDK) calibrated down to 77 K under silicon measurements. The DMTJ-based SIMPLY demonstrates a significant improvement in read margin at 77 K, overcoming the conventional SIMPLY scheme at room temperature (300 K) by approximately 2.3 X. When implementing logic operations with the SIMPLY scheme operating at 77 K, the DMTJ-based scheme assures energy savings of about 69%, as compared to its SMTJ-based counterpart operating at 77 K. Overall, our results prove that the SIMPLY scheme at cryogenic conditions is a promising solution for reliable and energy-efficient logic-in-memory (LIM) architectures.

Indexed as

77 KcryogenicDMTJIMPLYin-memory computinglogic-in-memorymagnetic tunnel junctionmaterial implicationSIMPLYSMTJSTT-MRAM

Identifiers

PMID39791768
PMCPMC11722062

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.