45 citations · 228 across the 26 of their papers we have counts for
40 papers
Design Rules for Extreme-Edge Scientific Computing on AI Engines
Zhenghua Ma, G Abarajithan, Dimitrios Danopoulos +3
Extreme-edge scientific applications use machine learning models to analyze sensor data and make real-time decisions. Their stringent latency and throughput requirements demand sma…
FireBridge: Cycle-Accurate Hardware + Firmware Co-Verification for Modern Accelerators
G Abarajithan, Zhenghua Ma, Francesco Restuccia +1
Hardware-firmware integration is becoming a productivity bottleneck due to the increasing complexity of accelerators, characterized by intricate memory hierarchies and firmware-int…
TinySense: Effective CSI Compression for Scalable and Accurate Wi-Fi Sensing
Toan Gian, Dung T. Tran, Viet Quoc Pham +2
With the growing demand for device-free and privacy-preserving sensing solutions, Wi-Fi sensing has emerged as a promising approach for human pose estimation (HPE). However, existi…
Semantic Multiplexing
Mohammad Abdi, Francesca Meneghello, Francesco Restuccia
Mobile devices increasingly require the parallel execution of several computing tasks offloaded at the wireless edge. Existing communication systems only support parallel transmiss…
A Reliable, Time-Predictable Heterogeneous SoC for AI-Enhanced Mixed-Criticality Edge Applications
Angelo Garofalo, Alessandro Ottaviano, Matteo Perotti +20
Next-generation mixed-criticality Systems-on-chip (SoCs) for robotics, automotive, and space must execute mixed-criticality AI-enhanced sensor processing and control workloads, ens…
AXI-REALM: Safe, Modular and Lightweight Traffic Monitoring and Regulation for Heterogeneous Mixed-Criticality Systems
Thomas Benz, Alessandro Ottaviano, Chaoqun Liang +6
The automotive industry is transitioning from federated, homogeneous, interconnected devices to integrated, heterogeneous, mixed-criticality systems (MCS). This leads to challenges…