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Data Direct Networks

NVIDIA CHOOSES DDN FOR FLAGSHIP AI SUPERCOMPUTER

NVIDIA GPU 1999

Since NVIDIA’s invention of the GPU in 1999, the company has set new standards.

These standards include computing innovation, deep-learning and data analytics.

With the introduction of the NVIDIA DGX™ A100, NVIDIA raised the bar once more.

By consolidating the power of an entire data center into a single platform, NVIDIA is revolutionizing how complex machine learning workflows and AI models are developed and deployed in an enterprise.

NVIDIA Selene DDN

This computing marvel also led to the creation of Selene.

Selene is the world’s seventh fastest computer in total performance and the world’s fastest commercially-available system - the NVIDIA DGX SuperPOD™ Solution. DGX A100 systems are being used to fight COVID-19, fuel autonomous vehicles, develop superhuman language understanding, and transform almost every facet of business with AI.

“Having a partner who stands shoulder-to-shoulder with our engineers to solve the big challenges is where the true value comes from. We’re definitely pushing the boundaries of what’s possible today with DDN while exploring new frontiers for the future.”

~ Michael Houston

Chief Architect - AI Systems

DDN AND NVIDIA PRESENT

HOW TO BUILD AN AI SUPERCOMPUTER IN WEEKS

Featuring NVIDIA’s DGX SuperPOD™ Solution with DDN Technology.

DDN NVIDIA
DDN NVIDIA Success Story
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World’s most advanced system drives AI at-scale discovery, development, and deployment breakthroughs

The Challenge

01

Extremely fast storage needed to fuel the exponential growth of AI models, drive increasing demand for higher data rates per GPU and I/O bandwidth

02

High degrees of parallel access to small and large datasets necessitated balanced storage performance

03

Storage architecture flexibility with easy horizontal scalability required for incremental and on-demand data center expansion

The Solution

01

DDN’s AI400X delivers scalable petabytes of powerful storage for NVIDIA Selene and NVIDIA DGX SuperPOD

02

Extremely fast storage needed to fuel the exponential growth of AI models, drive increasing demand for higher data rates per GPU and I/O bandwidth

03

High degrees of parallel access to small and large datasets necessitated balanced storage performance

The Benefits

01

Dramatic increase in AI workload performance enables organizations to iterate faster and boost data science productivity

02

Modular platform ensures AI infrastructure scalability with greater speed and cost efficiency

03

Fully integrated AI reference architectures democratize AI infrastructure for diverse workloads with streamlined deployment and operation

Find Out More

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