Top-Down Profiling of Application Specific Many-core Neuromorphic Platforms. - Gianvito Urgese; Francesco Barchi; Enrico Macii (MCSoC, 2015)

Toolchain integration of runtime variability and aging awareness in multicore platforms. - Ramakrishna Venkata Nittala; Francesco Barchi; Gianvito Urgese; Andrea Acquaviva (FDL, 2016)

Data and Commands Communication Protocol for Neuromorphic Platform Configuration. - Alessandro Siino; Francesco Barchi; Sergio Davies; Gianvito Urgese; Andrea Acquaviva (MCSoC, 2016)

An Efficient MPI Implementation for Multi-Coreneuromorphic Platforms. - Francesco Barchi; Gianvito Urgese; Enrico Macii; Andrea Acquaviva (NGCAS, 2017)

Impact of graph partitioning on SNN placement for a multi-core neuromorphic architecture: work-in-progress. - Francesco Barchi; Gianvito Urgese; Enrico Macii; Andrea Acquaviva (CASES, 2018)

Multiple alignment of packet sequences for efficient communication in a many-core neuromorphic system: work-in-progress. - Gianvito Urgese; Luca Peres; Francesco Barchi; Enrico Macii; Andrea Acquaviva (CASES, 2018)

Directed Graph Placement for SNN Simulation into a multi-core GALS Architecture. - Francesco Barchi; Gianvito Urgese; Andrea Acquaviva; Enrico Macii (VLSI-SoC, 2018)

Mapping Spiking Neural Networks on Multi-core Neuromorphic Platforms: Problem Formulation and Performance Analysis. - Francesco Barchi; Gianvito Urgese; Enrico Macii; Andrea Acquaviva (VLSI-SoC (Selected Papers), 2018)

Optimizing Network Traffic for Spiking Neural Network Simulations on Densely Interconnected Many-Core Neuromorphic Platforms. - Gianvito Urgese; Francesco Barchi; Enrico Macii; Andrea Acquaviva (IEEE Trans. Emerg. Top. Comput., 2018)

Code Mapping in Heterogeneous Platforms Using Deep Learning and LLVM-IR. - Francesco Barchi; Gianvito Urgese; Enrico Macii; Andrea Acquaviva (DAC, 2019)

Source Code Classification for Energy Efficiency in Parallel Ultra Low-Power Microcontrollers. - Emanuele Parisi; Francesco Barchi; Andrea Bartolini; Giuseppe Tagliavini; Andrea Acquaviva (DATE, 2021)

Damage Detection in Structural Health Monitoring with Spiking Neural Networks. - Luca Zanatta; Francesco Barchi; Alessio Burrello; Andrea Bartolini; Davide Brunelli; Andrea Acquaviva (MetroInd4.0&IoT, 2021)

Exploration of Convolutional Neural Network models for source code classification. - Francesco Barchi; Emanuele Parisi; Gianvito Urgese; Elisa Ficarra; Andrea Acquaviva (Eng. Appl. Artif. Intell., 2021)

Spiking Neural Network-Based Near-Sensor Computing for Damage Detection in Structural Health Monitoring. - Francesco Barchi; Luca Zanatta; Emanuele Parisi; Alessio Burrello; Davide Brunelli; Andrea Bartolini; Andrea Acquaviva (Future Internet, 2021)

Flexible On-Line Reconfiguration of Multi-Core Neuromorphic Platforms. - Francesco Barchi; Gianvito Urgese; Alessandro Siino; Santa Di Cataldo; Enrico Macii; Andrea Acquaviva (IEEE Trans. Emerg. Top. Comput., 2021)

Smart Contracts for Certified and Sustainable Safety-Critical Continuous Monitoring Applications. - Nicola Elia; Francesco Barchi; Emanuele Parisi; Livio Pompianu; Salvatore Carta; Andrea Bartolini; Andrea Acquaviva (ADBIS, 2022)

Meet Monte Cimone: exploring RISC-V high performance compute clusters. - Federico Ficarelli; Andrea Bartolini; Emanuele Parisi; Francesco Beneventi; Francesco Barchi; Daniele Gregori; Fabrizio Magugliani; Marco Cicala; Cosimo Gianfreda; Daniele Cesarini; Andrea Acquaviva; Luca Benini (CF, 2022)

Artificial versus spiking neural networks for reinforcement learning in UAV obstacle avoidance. - Luca Zanatta; Francesco Barchi; Andrea Bartolini; Andrea Acquaviva (CF, 2022)

Time and Frequency Domain Assessment of Low-Power MEMS Accelerometers for Structural Health Monitoring. - Emanuele Parisi; Amirhossein Moallemi; Francesco Barchi; Andrea Bartolini; Davide Brunelli; Nicola Buratti; Andrea Acquaviva (MetroInd4.0& IoT, 2022)

Monte Cimone: Paving the Road for the First Generation of RISC-V High-Performance Computers. - Andrea Bartolini; Federico Ficarelli; Emanuele Parisi; Francesco Beneventi; Francesco Barchi; Daniele Gregori; Fabrizio Magugliani; Marco Cicala; Cosimo Gianfreda; Daniele Cesarini; Andrea Acquaviva; Luca Benini (SOCC, 2022)

Making the Most of Scarce Input Data in Deep Learning-Based Source Code Classification for Heterogeneous Device Mapping. - Emanuele Parisi; Francesco Barchi; Andrea Bartolini; Andrea Acquaviva (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2022)

RUST-Encoded Stream Ciphers on a RISC-V Parallel Ultra-Low-Power Processor (Invited Paper). - Francesco Barchi; Giacomo Pasini; Emanuele Parisi; Giuseppe Tagliavini; Andrea Bartolini; Andrea Acquaviva (PARMA-DITAM, 2023)

On the Containerization and Orchestration of RISC-V architectures for Edge-Cloud computing. - Francesco Lumpp; Francesco Barchi; Andrea Acquaviva; Nicola Bombieri (eSAAM, 2023)

RISC-V Processor Technologies for Aerospace Applications in the ISOLDE Project. - William Fornaciari; Federico Reghenzani; Giovanni Agosta; Davide Zoni; Andrea Galimberti; Francesco Conti 001; Yvan Tortorella; Emanuele Parisi; Francesco Barchi; Andrea Bartolini; Andrea Acquaviva; Daniele Gregori; et al. (SAMOS, 2023)

A Survey on Design Methodologies for Accelerating Deep Learning on Heterogeneous Architectures. - Fabrizio Ferrandi; Serena Curzel; Leandro Fiorin; Daniele Ielmini; Cristina Silvano; Francesco Conti 001; Alessio Burrello; Francesco Barchi; Luca Benini; Luciano Lavagno; Teodoro Urso; Enrico Calore; et al. (CoRR, 2023)

M100 dataset: time-aggregated data for anomaly detection. - Andrea Borghesi; Carmine Di Santi; Martin Molan; Mohsen Seyedkazemi Ardebili; Alessio Mauri; Massimiliano Guarrasi; Daniela Galetti; Mirko Cestari; Francesco Barchi; Luca Benini; Francesco Beneventi; Andrea Bartolini (Zenodo, 2023)

M100 dataset 1: from 20-03 to 20-12. - Andrea Borghesi; Carmine Di Santi; Martin Molan; Mohsen Seyedkazemi Ardebili; Alessio Mauri; Massimiliano Guarrasi; Daniela Galetti; Mirko Cestari; Francesco Barchi; Luca Benini; Francesco Beneventi; Andrea Bartolini (Zenodo, 2023)

M100 dataset 2: from 21-01 to 21-06. - Andrea Borghesi; Carmine Di Santi; Martin Molan; Mohsen Seyedkazemi Ardebili; Alessio Mauri; Massimiliano Guarrasi; Daniela Galetti; Mirko Cestari; Francesco Barchi; Luca Benini; Francesco Beneventi; Andrea Bartolini (Zenodo, 2023)

M100 dataset 3: from 21-07 to 21-09. - Andrea Borghesi; Carmine Di Santi; Martin Molan; Mohsen Seyedkazemi Ardebili; Alessio Mauri; Massimiliano Guarrasi; Daniela Galetti; Mirko Cestari; Francesco Barchi; Luca Benini; Francesco Beneventi; Andrea Bartolini (Zenodo, 2023)

M100 dataset 4: from 21-10 to 21-12. - Andrea Borghesi; Carmine Di Santi; Martin Molan; Mohsen Seyedkazemi Ardebili; Alessio Mauri; Massimiliano Guarrasi; Daniela Galetti; Mirko Cestari; Francesco Barchi; Luca Benini; Francesco Beneventi; Andrea Bartolini (Zenodo, 2023)

M100 dataset 5: from 22-01 to 22-02. - Andrea Borghesi; Carmine Di Santi; Martin Molan; Mohsen Seyedkazemi Ardebili; Alessio Mauri; Massimiliano Guarrasi; Daniela Galetti; Mirko Cestari; Francesco Barchi; Luca Benini; Francesco Beneventi; Andrea Bartolini (Zenodo, 2023)

M100 dataset 6: 22-03. - Andrea Borghesi; Carmine Di Santi; Martin Molan; Mohsen Seyedkazemi Ardebili; Alessio Mauri; Massimiliano Guarrasi; Daniela Galetti; Mirko Cestari; Francesco Barchi; Luca Benini; Francesco Beneventi; Andrea Bartolini (Zenodo, 2023)

M100 dataset 7: 22-04. - Andrea Borghesi; Carmine Di Santi; Martin Molan; Mohsen Seyedkazemi Ardebili; Alessio Mauri; Massimiliano Guarrasi; Daniela Galetti; Mirko Cestari; Francesco Barchi; Luca Benini; Francesco Beneventi; Andrea Bartolini (Zenodo, 2023)

M100 dataset 8: 22-05. - Andrea Borghesi; Carmine Di Santi; Martin Molan; Mohsen Seyedkazemi Ardebili; Alessio Mauri; Massimiliano Guarrasi; Daniela Galetti; Mirko Cestari; Francesco Barchi; Luca Benini; Francesco Beneventi; Andrea Bartolini (Zenodo, 2023)

M100 dataset 9: 22-06. - Andrea Borghesi; Carmine Di Santi; Martin Molan; Mohsen Seyedkazemi Ardebili; Alessio Mauri; Massimiliano Guarrasi; Daniela Galetti; Mirko Cestari; Francesco Barchi; Luca Benini; Francesco Beneventi; Andrea Bartolini (Zenodo, 2023)

M100 dataset 10: 22-07. - Andrea Borghesi; Carmine Di Santi; Martin Molan; Mohsen Seyedkazemi Ardebili; Alessio Mauri; Massimiliano Guarrasi; Daniela Galetti; Mirko Cestari; Francesco Barchi; Luca Benini; Francesco Beneventi; Andrea Bartolini (Zenodo, 2023)

M100 dataset 11: 22-08. - Andrea Borghesi; Carmine Di Santi; Martin Molan; Mohsen Seyedkazemi Ardebili; Alessio Mauri; Massimiliano Guarrasi; Daniela Galetti; Mirko Cestari; Francesco Barchi; Luca Benini; Francesco Beneventi; Andrea Bartolini (Zenodo, 2023)

M100 dataset 12: 22-09. - Andrea Borghesi; Carmine Di Santi; Martin Molan; Mohsen Seyedkazemi Ardebili; Alessio Mauri; Massimiliano Guarrasi; Daniela Galetti; Mirko Cestari; Francesco Barchi; Luca Benini; Francesco Beneventi; Andrea Bartolini (Zenodo, 2023)

Directly-trained Spiking Neural Networks for Deep Reinforcement Learning: Energy efficient implementation of event-based obstacle avoidance on a neuromorphic accelerator. - Luca Zanatta; Alfio Di Mauro; Francesco Barchi; Andrea Bartolini; Luca Benini; Andrea Acquaviva (Neurocomputing, 2023)

Towards the DT of an Educational Building: An AI-Based Distributed Measurement System for the Power Forecasting. - Virginia Negri; Samuel Zanella; Alessandro Mingotti; Roberto Tinarelli; Lorenzo Peretto; Francesco Barchi; Andrea Acquaviva (AMPS, 2024)

TinyLid: a RISC-V accelerated Neural Network For LiDAR Contaminant Classification in Autonomous Vehicle. - Grafika Jati; Martin Molan; Francesco Barchi; Andrea Bartolini; Andrea Acquaviva (CF, 2024)

Assessing the Performance of OpenTitan as Cryptographic Accelerator in Secure Open-Hardware System-on-Chips. - Emanuele Parisi; Alberto Musa; Maicol Ciani; Francesco Barchi; Davide Rossi; Andrea Bartolini; Andrea Acquaviva (CF, 2024)

Towards Nano-Drones Agile Flight Using Deep Reinforcement Learning. - Sebastiano Mengozzi; Luca Zanatta; Francesco Barchi; Andrea Bartolini; Andrea Acquaviva (COINS, 2024)

TitanCFI: Toward Enforcing Control-Flow Integrity in the Root -of- Trust. - Emanuele Parisi; Alberto Musa; Simone Manoni; Maicol Ciani; Davide Rossi; Francesco Barchi; Andrea Bartolini; Andrea Acquaviva (DATE, 2024)

DeepCodeGraph: A Language Model for Compile-Time Resource Optimization Using Masked Graph Autoencoders. - Federico Cichetti; Emanuele Parisi; Andrea Acquaviva; Francesco Barchi (NLDB (1), 2024)

TitanSSL: Towards Accelerating OpenSSL in a Full RISC-V Architecture Using OpenTitan Root-of-Trust. - Alberto Musa; Franco Volante; Emanuele Parisi; Luca Barbierato; Edoardo Patti; Andrea Bartolini; Andrea Acquaviva; Francesco Barchi (SAFECOMP, 2024)

End-to-end Integration of OpenTitan Security Features in a Pure RISC-V SoC. - Alberto Musa; Emanuele Parisi; Luca Barbierato; Andrea Acquaviva; Francesco Barchi (SMACD, 2024)

OP-TEE powered OpenSSL Engine enhancing Digital Signature security for ARM Architectures. - Franco Volante; Francesco Barchi; Edoardo Patti; Lorenzo Bottaccioli; Luca Barbierato (SMACD, 2024)

AutoGrAN: Autonomous Vehicle LiDAR Contaminant Detection using Graph Attention Networks. - Grafika Jati; Martin Molan; Junaid Ahmed Khan; Francesco Barchi; Andrea Bartolini; Giuseppe Mercurio; Andrea Acquaviva (ICPE (Companion), 2024)

Unleashing OpenTitan's Potential: a Silicon-Ready Embedded Secure Element for Root of Trust and Cryptographic Offloading. - Maicol Ciani; Emanuele Parisi; Alberto Musa; Francesco Barchi; Andrea Bartolini; Ari Kulmala; Rafail Psiakis; Angelo Garofalo; Andrea Acquaviva; Davide Rossi (CoRR, 2024)

Enhancing workplace safety: A flexible approach for personal protective equipment monitoring. - Alessia Pisu; Nicola Elia; Livio Pompianu; Francesco Barchi; Andrea Acquaviva; Salvatore Carta (Expert Syst. Appl., 2024)

LIDAROC dataset 5m: Realistic LiDAR Cover Contamination Dataset for Enhancing Autonomous Vehicle Perception Reliability. - Grafika Jati; Martin Molan; Francesco Barchi; Andrea Bartolini; Giuseppe Mercurio; Andrea Acquaviva (Zenodo, 2024)

LIDAROC dataset 10m: Realistic LiDAR Cover Contamination Dataset for Enhancing Autonomous Vehicle Perception Reliability. - Grafika Jati; Martin Molan; Francesco Barchi; Andrea Bartolini; Giuseppe Mercurio; Andrea Acquaviva (Zenodo, 2024)

LIDAROC dataset 20m: Realistic LiDAR Cover Contamination Dataset for Enhancing Autonomous Vehicle Perception Reliability. - Grafika Jati; Martin Molan; Francesco Barchi; Andrea Bartolini; Giuseppe Mercurio; Andrea Acquaviva (Zenodo, 2024)

Energy efficient and low-latency spiking neural networks on embedded microcontrollers through spiking activity tuning. - Francesco Barchi; Emanuele Parisi; Luca Zanatta; Andrea Bartolini; Andrea Acquaviva (Neural Comput. Appl., 2024)

Bio-Inspired Drone Control: A Reinforcement Learning-Trained Spiking Neural Networks for Agile Navigation in Dynamic Environment. - Yin-Ching Lee; Sebastiano Mengozzi; Luca Zanatta; Andrea Bartolini; Andrea Acquaviva; Francesco Barchi (COINS, 2025)

Integrating OpenTitan as a Security Controller for Cryptographic Tasks in RISC-V SoCs. - Alberto Musa; Emanuele Parisi; Luca Barbierato; Edoardo Patti; Andrea Acquaviva; Francesco Barchi (ITASEC/SERICS, 2025)

ANZIL: Attention-based network for zero-risk inspection of LiDAR point cloud in self-driving cars. - Grafika Jati; Martin Molan; Francesco Barchi; Andrea Bartolini; Giuseppe Mercurio; Andrea Acquaviva (Expert Syst. Appl., 2025)