The Critical Role of Storage in Optimizing AI Training Workloads - 30 de octubre de 2024 - TecnoWebinars.com

This presentation examines the critical role of storage solutions in optimizing AI workloads, with a primary focus on storage-intensive AI training workloads. We will highlight how AI models interact with storage systems during training, focusing on data loading and checkpointing mechanisms. We will explore how AI frameworks like PyTorch utilize different storage connectors to access various storage solutions. Finally, the presentation will delve into the use of file-based storage and object storage in the context of AI training: Attendees will: - Gain a clear understanding of the critical role of storage in AI model training workloads - Understand how AI models interact with storage systems during training, focusing on data loading and checkpointing mechanisms - Learn how AI frameworks like PyTorch use different storage connectors to access various storage solutions. - Explore how file-based storage and object storage is used in AI training