TinyVers: A 0.8-17 TOPS/W, 1.7 μW-20 mW, Tiny Versatile System-on-chip with State-Retentive eMRAM for Machine Learning Inference at the Extreme Edge-Reference-Cited by-同舟云学术

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TinyVers: A 0.8-17 TOPS/W, 1.7 μW-20 mW, Tiny Versatile System-on-chip with State-Retentive eMRAM for Machine Learning Inference at the Extreme Edge

Published:2022-06-12 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE Symposium on VLSI Technology and Circuits (VLSI Technology and Circuits)
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Author:

Jain Vikram¹,Giraldo Sebastian¹,Roose Jaro De¹,Boons Bert²,Mei Linyan¹,Verhelst Marian¹

Affiliation:

1. KU Leuven,MICAS,Belgium

2. Magics Instruments,Belgium

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9830116/9830138/09830409.pdf?arnumber=9830409

Reference8 articles.

Cited by 17 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Fusion of memristor and digital compute-in-memory processing for energy-efficient edge computing;Science;2024-04-19

2. Pianissimo: A Sub-mW Class DNN Accelerator With Progressively Adjustable Bit-Precision;IEEE Access;2024

3. A Nonvolatile AI-Edge Processor With SLC–MLC Hybrid ReRAM Compute-in-Memory Macro Using Current–Voltage-Hybrid Readout Scheme;IEEE Journal of Solid-State Circuits;2024-01

4. Challenges in Circuits of Nonvolatile Compute-In-Memory for Edge AI Chips;2023 IEEE 66th International Midwest Symposium on Circuits and Systems (MWSCAS);2023-08-06

5. TinyVers: A Tiny Versatile System-on-Chip With State-Retentive eMRAM for ML Inference at the Extreme Edge;IEEE Journal of Solid-State Circuits;2023-08

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