5 papers
Beyond Foundation Models: Dimension-Aware Neural Architecture Search with Small-Data Representation Models for Cryocooler Lifetime Prediction
Gregor Molan, Grafika Jati, Francesco Barchi +3
Large-scale pretrained time-series models achieve strong results through large-scale pretraining and task-agnostic representation learning, but they rely on abundant, diverse data…
Physics-Informed Neural Networks for Nonlinear Output Regulation
Sebastiano Mengozzi, Giovanni B. Esposito, Michelangelo Bin +3
This work addresses the full-information output regulation problem for nonlinear systems, assuming the states of both the plant and the exosystem are known. In this setting, perfec…
CVA6-CFI: A First Glance at RISC-V Control-Flow Integrity Extensions
Simone Manoni, Emanuele Parisi, Riccardo Tedeschi +3
This work presents the first design, integration, and evaluation of the standard RISC-V extensions for Control-Flow Integrity (CFI). The Zicfiss and Zicfilp extensions aim at prote…
Monte Cimone v2: Down the Road of RISC-V High-Performance Computers
Emanuele Venieri, Simone Manoni, Gabriele Ceccolini +6
Many RISC-V (RV) platforms and SoCs have been announced in recent years targeting the HPC sector, but only a few of them are commercially available and engineered to fit the HPC re…
SpikeStream: Accelerating Spiking Neural Network Inference on RISC-V Clusters with Sparse Computation Extensions
Simone Manoni, Paul Scheffler, Luca Zanatta +3
Spiking Neural Network (SNN) inference has a clear potential for high energy efficiency as computation is triggered by events. However, the inherent sparsity of events poses challe…