The Parallel & Distributed Computing Lab (PDCL) conducts research at the intersection of high performance computing and big data processing. Our group works in the broad area of Parallel & Distributed ...

Concurrent and parallel systems form the bedrock of modern computational infrastructures, enabling vast improvements in processing speed, efficiency and scalability. By orchestrating multiple ...

Our research area includes the groups "Embedded Systems (EmbSys)", "Parallel and Distributed Systems (PVS)", and "Computer Networks and Network Security (NetSec)". We focus on enhancing the safety, ...

Distributed deep learning has emerged as an essential approach for training large-scale deep neural networks by utilising multiple computational nodes. This methodology partitions the workload either ...

Distributed applications enable heterogeneous environments with different systems and architectures. The advantages are platform independence, availability and scalability. The article shows the ...