XNOR-VSH: A Valley-Spin Hall Effect-Based Compact and Energy-Efficient Synaptic Crossbar Array for Binary Neural Networks Article Swipe
Karam Cho
,
Akul Malhotra
,
Sumeet Kumar Gupta
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1109/jxcdc.2023.3320677
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1109/jxcdc.2023.3320677
Binary neural networks (BNNs) have shown an immense promise for resource-constrained edge artificial intelligence (AI) platforms. However, prior designs typically either require two bit-cells to encode signed weights leading to an area overhead, or require complex peripheral circuitry. In this article, we address this issue by proposing a compact and low power in-memory computing (IMC) of XNOR-based dot products featuring signed weight encoding in a single bit-cell. Our approach utilizes valley-spin Hall (VSH) effect in monolayer tungsten di-selenide to design an XNOR bit-cell (named “XNOR-VSH”) with differential storage and access-transistor-less topology. We co-optimize the proposed VSH device and a memory array to enable robust in-memory dot product computations between signed binary inputs and signed binary weights with sense margin (SM). Our results show that the proposed XNOR-VSH array achieves 4.8%–9.0% and 37%–63% lower IMC latency and energy, respectively, with 49%–64% smaller area compared to spin-transfer-torque (STT)-magnetic random access memory (MRAM) and spin-orbit-torque (SOT)-MRAM based XNOR-arrays. We also present the impact of hardware non-idealities and process variations in XNOR-VSH on system-level accuracy for the trained ResNet-18 BNNs using the CIFAR-10 dataset.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1109/jxcdc.2023.3320677
- https://ieeexplore.ieee.org/ielx7/6570653/7076742/10268108.pdf
- OA Status
- gold
- Cited By
- 5
- References
- 28
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4387197032
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Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4387197032Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1109/jxcdc.2023.3320677Digital Object Identifier
- Title
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XNOR-VSH: A Valley-Spin Hall Effect-Based Compact and Energy-Efficient Synaptic Crossbar Array for Binary Neural NetworksWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2023Year of publication
- Publication date
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2023-09-29Full publication date if available
- Authors
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Karam Cho, Akul Malhotra, Sumeet Kumar GuptaList of authors in order
- Landing page
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https://doi.org/10.1109/jxcdc.2023.3320677Publisher landing page
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https://ieeexplore.ieee.org/ielx7/6570653/7076742/10268108.pdfDirect link to full text PDF
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://ieeexplore.ieee.org/ielx7/6570653/7076742/10268108.pdfDirect OA link when available
- Concepts
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XNOR gate, Computer science, Encoding (memory), Binary number, Topology (electrical circuits), Computer hardware, Logic gate, Electrical engineering, Artificial intelligence, Algorithm, NAND gate, Engineering, Mathematics, ArithmeticTop concepts (fields/topics) attached by OpenAlex
- Cited by
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5Total citation count in OpenAlex
- Citations by year (recent)
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2025: 2, 2024: 2, 2023: 1Per-year citation counts (last 5 years)
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28Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| primary_location.raw_type | journal-article |
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| primary_location.is_accepted | True |
| primary_location.is_published | True |
| primary_location.raw_source_name | IEEE Journal on Exploratory Solid-State Computational Devices and Circuits |
| primary_location.landing_page_url | https://doi.org/10.1109/jxcdc.2023.3320677 |
| publication_date | 2023-09-29 |
| publication_year | 2023 |
| referenced_works | https://openalex.org/W3139521791, https://openalex.org/W2896122000, https://openalex.org/W3042468132, https://openalex.org/W3208067593, https://openalex.org/W2300242332, https://openalex.org/W3000301330, https://openalex.org/W2798554798, https://openalex.org/W4225755231, https://openalex.org/W4205230840, https://openalex.org/W3195413970, https://openalex.org/W2930624726, https://openalex.org/W3175040915, https://openalex.org/W3113114492, https://openalex.org/W2996305698, https://openalex.org/W2057701641, https://openalex.org/W2803975251, https://openalex.org/W3006802526, https://openalex.org/W4200419998, https://openalex.org/W2096445739, https://openalex.org/W2803325289, https://openalex.org/W3187831751, https://openalex.org/W3026337110, https://openalex.org/W4312121016, https://openalex.org/W4285588914, https://openalex.org/W3177592084, https://openalex.org/W2088797290, https://openalex.org/W2799745003, https://openalex.org/W3103565263 |
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