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ORCIDFederico Rossi 0003
- > Home > Persons > Federico Rossi 0003
Publications
- 2024
[j6]Federico Rossi
, Cinzia Bernardeschi, Marco Cococcioni:
Neural networks in closed-loop systems: Verification using interval arithmetic and formal prover. Eng. Appl. Artif. Intell. 137: 109238 (2024)- [c11]Federico Rossi, Cinzia Bernardeschi, Marco Cococcioni, Maurizio Palmieri:
Towards Formal Verification of Neural Networks in Cyber-Physical Systems. NFM 2024: 207-222 - 2023
- [c10]Lorenzo Fiaschi, Federico Rossi, Marco Cococcioni, Sergio Saponara:
Speeding Up Non-archimedean Numerical Computations Using AVX-512 SIMD Instructions. ApplePies 2023: 62-67 - [c8]John L. Gustafson, Marco Cococcioni, Federico Rossi, Emanuele Ruffaldi, Sergio Saponara:
Decoding-Free Two-Input Arithmetic for Low-Precision Real Numbers. CoNGA 2023: 61-76 - [c7]Michele Piccoli, Davide Zoni, William Fornaciari, Giuseppe Massari, Marco Cococcioni, Federico Rossi, Sergio Saponara, Emanuele Ruffaldi:
Dynamic Power Consumption of the Full Posit Processing Unit: Analysis and Experiments. PARMA-DITAM 2023: 6:1-6:11 - [i2]Federico Rossi, Francesco Urbani, Marco Cococcioni, Emanuele Ruffaldi, Sergio Saponara:
FPPU: Design and Implementation of a Pipelined Full Posit Processing Unit. CoRR abs/2308.03425 (2023) - [i1]Federico Rossi, Marco Cococcioni, Roger Ferrer Ibáñez, Jesús Labarta, Filippo Mantovani, Marc Casas, Emanuele Ruffaldi, Sergio Saponara:
Compressed Real Numbers for AI: a case-study using a RISC-V CPU. CoRR abs/2309.07158 (2023) - 2022
- [j5]Marco Cococcioni, Federico Rossi, Emanuele Ruffaldi, Sergio Saponara:
A Lightweight Posit Processing Unit for RISC-V Processors in Deep Neural Network Applications. IEEE Trans. Emerg. Top. Comput. 10(4): 1898-1908 (2022) - [c6]Federico Rossi, Lorenzo Fiaschi, Marco Cococcioni, Sergio Saponara:
Design and FPGA Synthesis of BAN Processing Unit for Non-Archimedean Number Crunching. ApplePies 2022: 320-325 - [c5]Marco Cococcioni, Federico Rossi, Emanuele Ruffaldi, Sergio Saponara:
Small Reals Representations for Deep Learning at the Edge: A Comparison. CoNGA 2022: 117-133 - 2021
- [j4]Marco Cococcioni, Federico Rossi, Emanuele Ruffaldi, Sergio Saponara:
Vectorizing posit operations on RISC-V for faster deep neural networks: experiments and comparison with ARM SVE. Neural Comput. Appl. 33(16): 10575-10585 (2021) - [j3]Marco Cococcioni, Federico Rossi, Emanuele Ruffaldi, Sergio Saponara, Benoît Dupont de Dinechin:
Novel Arithmetics in Deep Neural Networks Signal Processing for Autonomous Driving: Challenges and Opportunities. IEEE Signal Process. Mag. 38(1): 97-110 (2021) - [c4]Marco Cococcioni, Federico Rossi, Emanuele Ruffaldi, Sergio Saponara:
Experimental Results of Vectorized Posit-Based DNNs on a Real ARM SVE High Performance Computing Machine. ApplePies 2021: 61-68 - 2020
- [j2]Marco Cococcioni, Federico Rossi, Emanuele Ruffaldi, Sergio Saponara:
Fast deep neural networks for image processing using posits and ARM scalable vector extension. J. Real Time Image Process. 17(3): 759-771 (2020) - [j1]Marco Cococcioni, Federico Rossi, Emanuele Ruffaldi, Sergio Saponara:
Fast Approximations of Activation Functions in Deep Neural Networks when using Posit Arithmetic. Sensors 20(5): 1515 (2020) - [c3]Marco Cococcioni, Federico Rossi, Emanuele Ruffaldi, Sergio Saponara:
A Novel Posit-based Fast Approximation of ELU Activation Function for Deep Neural Networks. SMARTCOMP 2020: 244-246 - 2019
- [c2]Marco Cococcioni, Federico Rossi, Emanuele Ruffaldi, Sergio Saponara:
A Fast Approximation of the Hyperbolic Tangent When Using Posit Numbers and Its Application to Deep Neural Networks. ApplePies 2019: 213-221 - [c1]Marco Cococcioni, Federico Rossi, Emanuele Ruffaldi, Sergio Saponara:
Novel Arithmetics to Accelerate Machine Learning Classifiers in Autonomous Driving Applications. ICECS 2019: 779-782
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