ONTAP Data Management for Deep Learning Workloads

This white paper presents the architectural vision for NetApp ONTAP, focusing on its capabilities to manage unstructured data in the context of deep learning and Generative AI. It outlines the challenges posed by the increasing volume of unstructured data, which constitutes 80% of the 400 million terabytes generated daily. The document details how deep learning architectures necessitate high throughput and performance, driving the need for innovative data management solutions. It describes the evolution of data-driven architectures and the importance of disaggregated infrastructure to efficiently handle data processing and management at scale. The paper further explains the AI Data Platform powered by ONTAP, which is designed to support high bandwidth and scalability for deep learning applications. It emphasizes the integration of Intelligent Data functions within ONTAP to provide a structured view of unstructured data, thereby facilitating seamless interaction with AI ecosystems. The architectural tenets of this new framework are also discussed, highlighting the need for a single pool of storage and the benefits of composable architecture.