This session examines the role of modern parallel file systems in supporting scalable, data-intensive HPC environments commonly found in academic and regional research computing centers. It discusses how BeeGFS enables high-throughput, low-latency storage architectures that effectively support a wide range of workloads, including traditional simulation, modeling, data analytics, and emerging AI-driven research. Attendees will gain insight into BeeGFS architecture and design principles, including scalable metadata services, flexible storage tiering, and integration with high-speed networks and NVMe-based storage. The session will also present real-world user case studies from research and HPC environments, highlighting practical deployment considerations, performance characteristics, and operational lessons learned. By focusing on production deployments and real research workflows, this talk demonstrates how BeeGFS is used today to build reliable, high-performance storage platforms that scale with growing compute and data demands in academic and research-focused HPC environments.
