11 papers
EFFEKT: Efficient Federated Knowledge Transfer to Foundation Models
Matteo Caligiuri, Francesco Barbato, Pietro Zanuttigh +1
Recent data protection laws have accelerated the adoption of Federated Learning (FL) for privacy-preserving decentralized training. Nevertheless, increasing model sizes impose subs…
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…
CGRA4ML: A Hardware/Software Framework to Implement Neural Networks for Scientific Edge Computing
G Abarajithan, Zhenghua Ma, Ravidu Munasinghe +2
The scientific community increasingly relies on machine learning (ML) for near-sensor processing, leveraging its strengths in tasks such as pattern recognition, anomaly detection,…
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…