On-device Online Learning and Semantic Management of TinyML Systems
Recent advances in Tiny Machine Learning (TinyML) empower low-footprint embedded devices for real-time on-device Machine Learning (ML). While many acknowledge the potential benefits of TinyML, its practical implementation presents unique challenges. This ...
Lightweight Hardware-Based Cache Side-Channel Attack Detection for Edge Devices (Edge-CaSCADe)
Cache Side-Channel Attacks (CSCAs) have been haunting most processor architectures for decades now. Existing approaches to mitigation of such attacks have certain drawbacks, namely software mishandling, performance overhead, and low throughput due to ...
Coupling bit and modular arithmetic for efficient general-purpose fully homomorphic encryption
Fully Homomorphic Encryption (FHE) enables computation directly on encrypted data. This property is desirable for outsourced computation of sensitive data as it relies solely on the underlying security of the cryptosystem and not in access control ...
A Review of Abstraction Methods Toward Verifying Neural Networks
Neural networks as a machine learning technique are increasingly deployed in various domains. Despite their performance and their continuous improvement, the deployment of neural networks in safety-critical systems, in particular for autonomous mobility, ...
Elements of Timed Pattern Matching
The rise of machine learning and cloud technologies has led to a remarkable influx of data within modern cyber-physical systems. However, extracting meaningful information from this data has become a significant challenge due to its volume and complexity. ...
CARIn: Constraint-Aware and Responsive Inference on Heterogeneous Devices for Single- and Multi-DNN Workloads
The relentless expansion of deep learning applications in recent years has prompted a pivotal shift toward on-device execution, driven by the urgent need for real-time processing, heightened privacy concerns, and reduced latency across diverse domains. ...
TREAFET: Temperature-Aware Real-Time Task Scheduling for FinFET based Multicores
The recent shift in the VLSI industry from conventional MOSFET to FinFET for designing contemporary chip-multiprocessor (CMP) has noticeably improved hardware platforms’ computing capabilities, but at the cost of several thermal issues. Unlike the ...
Multi-Traffic Resource Optimization for Real-Time Applications with 5G Configured Grant Scheduling
The fifth-generation (5G) technology standard in telecommunications is expected to support ultra-reliable low latency communication to enable real-time applications such as industrial automation and control. 5G configured grant (CG) scheduling features a ...
