136 citations · 283 across the 19 of their papers we have counts for
6 papers · 1 filter
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…
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…
ARCANE: Adaptive RISC-V Cache Architecture for Near-memory Extensions
Vincenzo Petrolo, Flavia Guella, Michele Caon +3
Modern data-driven applications expose limitations of von Neumann architectures - extensive data movement, low throughput, and poor energy efficiency. Accelerators improve performa…
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…