17 citations · 28 across the 12 of their papers we have counts for
12 papers
Enabling Ultra-Low-Power Always-On Feedforward Leakage Suppression Logic Circuits with FDSOI
Clément Choné, Leslie Xu, Filippo Quadri +5
The growing deployment of real-time applications on wearable and Internet of Things (IoT) edge devices has intensified the need for energy-efficient, high-performance systems that…
X-HEEP: An Open-Source, Configurable and Extendible RISC-V Platform for TinyAI Applications
Simone Machetti, Pasquale Davide Schiavone, Giovanni Ansaloni +2
In this work, we present X-HEEP, an open-source, configurable, and extendible RISC-V platform for ultra-low-power edge applications (TinyAI). X-HEEP features the eXtendible Acceler…
CEO-DC: Driving Decarbonization in HPC Data Centers with Actionable Insights
Rubén Rodríguez Álvarez, Denisa-Andreea Constantinescu, Miguel Peón-Quirós +1
The rapid growth of data centers is increasing energy demand and widening the carbon gap in the ICT sector, as fossil fuels still dominate global energy production. Addressing this…
e-GPU: An Open-Source and Configurable RISC-V Graphic Processing Unit for TinyAI Applications
Simone Machetti, Pasquale Davide Schiavone, Lara Orlandic +4
Graphics processing units (GPUs) excel at parallel processing, but remain largely unexplored in ultra-low-power edge devices (TinyAI) due to their power and area limitations, as we…
Quadrilatero: A RISC-V programmable matrix coprocessor for low-power edge applications
Danilo Cammarata, Matteo Perotti, Marco Bertuletti +4
The rapid growth of AI-based Internet-of-Things applications increased the demand for high-performance edge processing engines on a low-power budget and tight area constraints. As…
Just TestIt! An SBST Approach To Automate System-Integration Testing
Tommaso Terzano, Luigi Giuffrida, Juan Sapriza +5
This paper introduces TestIt, an open-source Python package designed to automate full-system integration testing using a Software-Based Self-Test (SBST) approach. By dynamically ge…
Increasing the Energy-Efficiency of Wearables Using Low-Precision Posit Arithmetic with PHEE
David Mallasén, Pasquale Davide Schiavone, Alberto A. Del Barrio +2
Wearable edge AI biomedical devices are increasingly being used for continuous patient health monitoring, enabling real-time insights and extended data collection without the need…
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…