activity
20202023
collaborators

5 papers

cs.LG2023

Partitioning Distributed Compute Jobs with Reinforcement Learning and Graph Neural Networks

Christopher W. F. Parsonson, Zacharaya Shabka, Alessandro Ottino +1

From natural language processing to genome sequencing, large-scale machine learning models are bringing advances to a broad range of fields. Many of these models are too large to b…

cs.NI2022

Network Aware Compute and Memory Allocation in Optically Composable Data Centres with Deep Reinforcement Learning and Graph Neural Networks

Zacharaya Shabka, Georgios Zervas

Resource-disaggregated data centre architectures promise a means of pooling resources remotely within data centres, allowing for both more flexibility and resource efficiency under…

eess.SY2022

One-shot, Offline and Production-Scalable PID Optimisation with Deep Reinforcement Learning

Zacharaya Shabka, Michael Enrico, Nick Parsons +1

Proportional-integral-derivative (PID) control underlies more than of automated industrial processes. Controlling these processes effectively with respect to some specified…

cs.LG2021

Resource Allocation in Disaggregated Data Centre Systems with Reinforcement Learning

Zacharaya Shabka, Georgios Zervas

Resource-disaggregated data centres (RDDC) propose a resource-centric, and high-utilisation architecture for data centres (DC), avoiding resource fragmentation and enabling arbitra…

eess.SP2020

SWIFT: Scalable Ultra-Wideband Sub-Nanosecond Wavelength Switching for Data Centre Networks

Thomas Gerard, Christopher Parsonson, Zacharaya Shabka +3

We propose a time-multiplexed DS-DBR/SOA-gated system to deliver low-power fast tuning across S-/C-/L-bands. Sub-ns switching is demonstrated, supporting 12250 GHz channels…