17 citations · 28 across the 12 of their papers we have counts for
5 papers · 1 filter
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…
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…
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…
Performance evaluation of acceleration of convolutional layers on OpenEdgeCGRA
Nicolò Carpentieri, Juan Sapriza, Davide Schiavone +4
Recently, efficiently deploying deep learning solutions on the edge has received increasing attention. New platforms are emerging to support the increasing demand for flexibility a…
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…