From bytes to breakthroughs: Data storage challenges in scientific research
Scientific research is generating more data than ever before.
From AI and machine learning to simulation and genomics, research teams must manage petabytes of data while maintaining performance, security and cost efficiency.
But choosing the right storage strategy is becoming increasingly complex.
Should you prioritise high-performance NVMe, scalable tiered storage, or cloud solutions?
How will AI workloads reshape infrastructure requirements?
And how are leading research institutions solving these challenges today?
What you’ll learn
In this expert roundtable report, research computing leaders share how they are managing data storage in modern HPC environments.
Inside the report:
- How leading research institutions design tiered storage architectures
- The key factors influencing storage infrastructure decisions
- How AI and GPU workloads are changing storage requirements
- Why many research organisations remain cautious about cloud storage
- What experts believe the future of research data storage will look like
The report features insights from HPC leaders at organisations including the University of Cambridge, Lund University and Simula Research Laboratory.
Who should download this report
This white paper is designed for:
- HPC and research computing leaders
- Data centre architects
- Research IT and infrastructure teams
- AI and data platform specialists
- University and laboratory technology managers
If you support data-intensive scientific computing environments, this report provides valuable peer insights.
Download the white paper
From bytes to breakthroughs: Data storage challenges in scientific research
Gain practical insights into how research organisations are preparing their infrastructure for the next wave of data-driven discovery.
