Publications (5)
The Role of Cross-Silo Federated Learning in Facilitating Data Sharing in the Agri-Food Sector
Aiden Durrant, Milan Markovic, David Matthews +3
Data sharing remains a major hindering factor when it comes to adopting emerging AI technologies in general, but particularly in the agri-food sector. Protectiveness of data is nat…
Lost in translation: Exposing hidden compiler optimization opportunities
Kyriakos Georgiou, Zbigniew Chamski, Andres Amaya Garcia +2
Existing iterative compilation and machine-learning-based optimization techniques have been proven very successful in achieving better optimizations than the standard optimization…
Scalable data abstractions for distributed parallel computations
James Hanlon, Simon J. Hollis, David May
The ability to express a program as a hierarchical composition of parts is an essential tool in managing the complexity of software and a key abstraction this provides is to separa…
Hybrid machine learning based scale bridging framework for permeability prediction of fibrous structures
Denis Korolev, Tim Schmidt, Dinesh K. Natarajan +4
This study introduces a hybrid machine learning-based scale-bridging framework for predicting the permeability of fibrous textile structures. By addressing the computational challe…
A Benes Based NoC Switching Architecture for Mixed Criticality Embedded Systems
Steve Kerrison, David May, Kerstin Eder
Multi-core, Mixed Criticality Embedded (MCE) real-time systems require high timing precision and predictability to guarantee there will be no interference between tasks. These guar…