8 citations · 9 across the 9 of their papers we have counts for
3 papers · 1 filter
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…
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…
Efficient Trace for RISC-V: Design, Evaluation, and Integration in CVA6
Umberto Laghi, Simone Manoni, Emanuele Parisi +1
In this work, we present the design and evaluation of a Processor Tracing System compliant with the RISC-V Efficient Trace specification for Instruction Branch Tracing. We integrat…