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20162026
most citedXNOR Neural Engine: a Hardware Accelerator IP for 21.6 fJ/op Binary Neural Network Inference

136 citations · 283 across the 19 of their papers we have counts for

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Showing 2024Show all

6 papers · 1 filter

eess.SP2024

Enabling Efficient Wearables: An Analysis of Low-Power Microcontrollers for Biomedical Applications

Dimitrios Samakovlis, Stefano Albini, Rubén Rodríguez Álvarez +4

Breakthroughs in ultra-low-power chip technology are transforming biomedical wearables, making it possible to monitor patients in real time with devices operating on mere μW. Altho…

cs.LG2024★ 1 cited

MetaWearS: A Shortcut in Wearable Systems Lifecycle with Only a Few Shots

Alireza Amirshahi, Maedeh H. Toosi, Siamak Mohammadi +5

Wearable systems provide continuous health monitoring and can lead to early detection of potential health issues. However, the lifecycle of wearable systems faces several challenge…

cs.AR2024★ 17 cited

Scalable and RISC-V Programmable Near-Memory Computing Architectures for Edge Nodes

Michele Caon, Clément Choné, Pasquale Davide Schiavone +4

The widespread adoption of data-centric algorithms, particularly Artificial Intelligence (AI) and Machine Learning (ML), has exposed the limitations of centralized processing infra…

cs.LG2024

BiomedBench: A benchmark suite of TinyML biomedical applications for low-power wearables

Dimitrios Samakovlis, Stefano Albini, Rubén Rodríguez Álvarez +4

The design of low-power wearables for the biomedical domain has received a lot of attention in recent decades, as technological advances in chip manufacturing have allowed real-tim…

cs.AR2024

STRELA: STReaming ELAstic CGRA Accelerator for Embedded Systems

Daniel Vazquez, Jose Miranda, Alfonso Rodriguez +3

Reconfigurable computing offers a good balance between flexibility and energy efficiency. When combined with software-programmable devices such as CPUs, it is possible to obtain hi…

cs.AR2024★ 2 cited

X-HEEP: An Open-Source, Configurable and Extendible RISC-V Microcontroller for the Exploration of Ultra-Low-Power Edge Accelerators

Simone Machetti, Pasquale Davide Schiavone, Thomas Christoph Müller +2

The field of edge computing has witnessed remarkable growth owing to the increasing demand for real-time processing of data in applications. However, challenges persist due to limi…