no code implementations • 31 Jan 2023 • Christopher W. F. Parsonson, Zacharaya Shabka, Alessandro Ottino, Georgios Zervas
Many of these models are too large to be trained on a single machine, and instead must be distributed across multiple devices.
no code implementations • 26 Oct 2022 • 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 underlying the increasingly important infrastructure-as-a-service business.
no code implementations • 25 Oct 2022 • Zacharaya Shabka, Michael Enrico, Nick Parsons, Georgios Zervas
Furthermore, once trained (which takes $\mathcal{O}(hours)$), the model generates actuator-unique PID parameters in a one-shot inference process that takes $\mathcal{O}(ms)$ in comparison to up to $\mathcal{O}(week)$ required for conventional tuning methods, therefore accomplishing these performance improvements whilst achieving up to a $10^6\times$ speed-up.
no code implementations • 4 Jun 2021 • 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 arbitrarily sized resource pools to be allocated to tasks, rather than server-sized ones.
no code implementations • 22 Jun 2020 • Christopher W. F. Parsonson, Zacharaya Shabka, W. Konrad Chlupka, Bawang Goh, Georgios Zervas
Novel approaches to switching ultra-fast semiconductor optical amplifiers using artificial intelligence algorithms (particle swarm optimisation, ant colony optimisation, and a genetic algorithm) are developed and applied both in simulation and experiment.