Solving the AI Bottleneck: Storage Architectures that Keep GPUs Fed

In this technical session, we'll explore how VDURA's V5000 and VPOD architectures address the unique performance, scalability and compliance challenges of modern AI workloads. From metadata-intensive language model training to multi-model defense applications, we'll break down how unified namespaces, dynamic data acceleration and parallel I/O paths eliminate traditional constraints on AI pipelines.

Attendees will gain insight into:

• How to overcome metadata bottlenecks in large-scale training.
• Strategies for sustaining GPU saturation with 1 TB/s throughout per rack.
• Balancing training, interference and preprocessing workloads in a single infrastructure.
• Architecting for edge-to-core AI deployments in federal environments.
• Meeting governance and compliance requirements while scaling AI models.

Whether you're designing next-generation AI pipelines, optimizing multi-node training or tackling federal AI-specific challenges, this session will provide a blueprint for building storage architectures that deliver both performance and resilience at scale.