Scientific research infrastructures are facing a rapid escalation in data volumes generated by Artificial Intelligence and machine learning, large scale simulations and genomics, which is forcing research teams to manage petabytes of data while maintaining performance, security and cost efficiency. Storage strategy decisions are becoming more complex as organisations weigh high performance NVMe, scalable tiered storage and cloud based options, and must also consider how Artificial Intelligence workloads will reshape infrastructure requirements. Research computing leaders are increasingly focused on aligning storage capabilities with high performance computing environments so that data intensive workflows are not constrained by bottlenecks.
An expert roundtable report brings together high performance computing leaders from organisations including the University of Cambridge, Lund University and Simula Research Laboratory to describe practical approaches to modern storage design. The report details how leading research institutions design tiered storage architectures that can match different performance and capacity needs, and it highlights the key factors influencing infrastructure choices, such as workload type, budget constraints and long term retention requirements. Contributors explain how Artificial Intelligence and GPU workloads are changing storage requirements, prompting demand for faster access to active data as well as scalable systems that can accommodate rapid growth without sacrificing reliability.
The roundtable also explores why many research organisations remain cautious about cloud storage despite its flexibility, citing concerns over cost predictability, data sovereignty and performance for large scale scientific workloads. The report is positioned as a white paper for high performance computing and research computing leaders, data centre architects, research IT and infrastructure teams, Artificial Intelligence and data platform specialists, and university and laboratory technology managers who support data intensive environments. Readers are promised peer insights into how research organisations are preparing infrastructure for the next wave of data driven discovery, including perspectives on what experts believe the future of research data storage will look like.
