Building data centre networks for AI workloads: key requirements and considerations for CSPs
11 October 2023 | Research
Strategy report | PPTX and PDF (6 slides) | Cloud and AI Infrastructure
As communications service providers (CSPs) train continuously larger AI models (especially generative AI models), models must be trained on an increasingly large number of graphics processing units (GPUs). CSPs that want to train these models in their own data centres will need to upgrade their back-end networks, that is, the networks which connect different GPUs within a data centre.
Information included in this report
- Insights into the back-end data centre networking requirements of AI workloads
- Analysis of the approaches to AI networking that CSPs can adopt in their data centres
Author

Joseph Attwood
AnalystRelated items
Strategy report
Private cloud AI infrastructure: requirements and strategies for telecoms operators and other enterprises
Tracker
Public cloud provider and CSP partnership tracker 2H 2024
Tracker
5G network cloud deployment tracker 3Q 2024