Lilly Tech Systems
Distributed File Systems for AI
Master high-performance parallel file systems that power large-scale AI training. Learn to deploy and optimize Lustre, GPFS/Spectrum Scale, BeeGFS, and NFS for GPU clusters and HPC environments.
Your Learning Path
Follow these lessons in order, or jump to any topic that interests you.
1. Introduction
Understand why AI workloads need distributed file systems and how parallel I/O accelerates training across GPU clusters.
2. Lustre
Deploy and configure Lustre for AI training with striping, OST management, and cloud-native options like Amazon FSx.
3. GPFS / Spectrum Scale
Configure IBM Spectrum Scale for enterprise AI with policy-based tiering, AFM, and multi-cluster federation.
4. BeeGFS
Set up BeeGFS for cost-effective parallel storage with buddy mirroring, striping, and GPU-direct storage integration.
5. NFS at Scale
Scale NFS for AI workloads using managed services, pNFS, caching strategies, and hybrid object storage tiering.
6. Best Practices
Select the right file system, optimize for AI I/O patterns, monitor performance, and plan capacity for growth.