How Will AI’s “iPhone Moment” Affect AI Data Management?

As the interest in AI continues to build in both popular culture and business, organizations face imminent choices in storing and managing AI data.

1. Businesses must make choices today that will affect their ability to compete over the next ten years. Those that are slow to adapt will be left behind.
2. Businesses at the forefront of AI transformation realize that centralizing their data and processing in an AI Center of Excellence is the preferred approach for efficiency, security, manageability, and innovation.
3. NVIDIA DGX™ systems with DDN A³I storage are an ideal blueprint for companies seeking to accelerate their AI journey by supplying repeatable, proven AI computing infrastructure.
4. The key to effectively implementing an AI center of excellence is ensuring the selection of proven and capable infrastructure which is purpose-built for maximizing AI applications.

In his keynote at last week’s GTC, NVIDIA’s CEO, Jensen Huang, declared that the explosive popularity of ChatGPT equivalent to an “iPhone moment.” Yet Large Language Models (LLMs) like ChatGPT are just one application of data-intensive AI that businesses are turning to for better products, customer service, and operations. Generative AI applications, metaverse simulations, and computer vision training are just some of the other use cases that demand access to large datasets and fast processing of that data.

The broad applicability of AI across virtually every market means businesses must make choices today that will affect their ability to compete over the next ten years. Organizations that are slow to adopt or invest in AI will see themselves left behind. At the core of these choices is how they handle the collection, transaction, processing, and storage of their data. If the process of digital transformation over the last 12 years led to substantial growth in data management requirements, AI transformation represents many orders of magnitude larger data explosion.

DDN has been there from the beginning. Prior to the most recent broad-based interest in AI emerging five or six years ago, DDN was working with AI researchers in academia and government institutions to optimize how data was stored and processed. Even before GPUs became the preferred processor of choice for AI workflows, parallel processing was the paramount approach. DDN established itself as the preeminent data storage provider for the most significant research organizations. The knowledge and experience gained in those environments were used to create AI storage solutions that accelerate AI computing and simplify data management at any scale.

Businesses at the forefront of AI transformation realize that centralizing their data and processing in an AI Center of Excellence is the preferred approach for efficiency, security, manageability, and innovation. By reducing silos between AI projects, a business can leverage its investment in AI computing and data storage across applications and create a data management regime that increases data governance and enhances the security and reliability of its data pipelines. The key to effectively implementing an AI center of excellence is ensuring the selection of proven and capable infrastructure which is purpose-built for maximizing AI applications.

Over the last five years, DDN has collaborated with NVIDIA to deliver DGX SuperPOD™ solutions to many of the largest AI developers worldwide and has shipped over 2.5 Exabytes of all-flash AI storage. These systems are an ideal blueprint for companies seeking to accelerate their AI journey by supplying repeatable, proven AI computing infrastructure. The announcement at GTC that NVIDIA DGX H100 systems are now coming online highlights the need for the storage capabilities provided by systems like DDN’s AI400X2. With 2X the networking connectivity and computing throughput, DDN’s parallel storage architecture ensures that the GPUs are running at maximum utilization while streamlining the management of data at a large scale. In addition, we have collaborated with NVIDIA to build unique enhancements, like DDN’s HotNodes, which further optimize the performance of AI applications.

DDN is also working to make AI infrastructure more accessible, as highlighted by a partnership with Lambda. Lambda supplies multiple routes to AI computing with solutions based on NVIDIA’s HGX and DGX GPU compute nodes and their newly announced GPU cloud service. These choices allow customers to select an AI computing infrastructure optimized to their exact needs with turnkey or on-demand deployment.

To learn more about how DDN has optimized its systems for AI computing and serves as the ideal foundation for your AI data, watch Dr. James Coomer’s GTC session, Unleash Lightning-Fast Storage for Unprecedented AI Efficiency and Performance (Presented by DDN) [S52439], on-demand at the NVIDIA GTC site. His session also contains a discussion with Lambda’s David Hall, Head of High Performance Computing, on their cloud architecture and why they chose DDN as the storage system to support their own deployment.