JTE Elms

10 years of DGX. 10 years of pushing AI infrastructure forward. 👏 When NVIDIA introduced DGX-1 in 2016, it created a new challenge: powerful GPUs needed data fast enough to keep them productive. That challenge helped shape DDN's evolution from supercomputing into AI infrastructure. From DDN A³I and Selene to DGX SuperPOD, Cambridge-1, Eos and today's next-generation AI architectures, the work has continued to evolve alongside accelerated computing. Learn the story of 10 years of DGX + DDN — and what comes next: bit.ly/4jA4yg4 #decadeofdgx

Your GPUs are only as powerful as the data feeding them. ⚡ At CoreWeave Fully Connected, Richard Ens, Ph.D, Client Director, Strategic AI at DDN, explains why AI pipelines need to look beyond GPU counts and models. As environments scale from a handful of GPUs to thousands, the data layer becomes critical to keeping GPUs fed, maintaining consistent performance, and improving time to first token. Watch to learn how the right AI Infrastructure can keep performance consistent as GPU footprints and models grow. ⬇️ #AIInfrastructure #FullyConnected2026

Eight years ago, DDN began working with @NVIDIA on a reference architecture that could show customers what was possible when industry-leading compute is paired with a high-performance data foundation. That moment marked the start of a powerful journey. As our CEO, Alex Bouzari, shares in this video, NVIDIA saw early on that AI performance depends on more than compute alone. It also depends on data. Together, DDN and NVIDIA have helped organizations turn AI investments into real business value, financial outcomes, and technological progress. #DecadeOfDGX

10 years of @NVIDIA DGX. A decade of pushing the boundaries of AI. 🎉 From the early days of deep learning to today's massive AI Factories, NVIDIA DGX has helped transform what's possible in AI. DDN is proud to work alongside NVIDIA to help organizations scale demanding AI workloads, accelerate innovation, and build the data foundation for what comes next. Here's to 10 years of NVIDIA DGX, a decade of incredible innovation, and many more breakthroughs ahead. #DecadeOfDGX

That's a wrap on HPC Roundtable in Turin! 👏 DDN was proud to join the HPC and AI community as a Gold Sponsor for a day of big ideas, great conversations, and a look at what's next for high-performance infrastructure. Antonio Colavincenzo of DDN, took the stage to share insights on advancing HPC and AI Infrastructure, with Daniele Maurizi also on the ground connecting with attendees. A big thank you to everyone who stopped by and joined the conversation! #HPCRoundtable #AIInfrastructure

GPUs should be working, not waiting. ⚡ DDN's Ifan Wibowo, is speaking at the @Vultr booth during Singapore Tech Week – Cloud & AI Infrastructure. In his session, “The Data Engine Powering the AI Economy,” he'll explore how GPU utilization, cost per token, and the data layer underneath compute are shaping AI economics. 🗓️ September 30 ⏰ 15:00 📍 Vultr Booth: #5-F25, level 5 ➡️ Join the session to learn how DDN helps organizations maximize GPU productivity and get more value from AI Infrastructure at any scale.

The AI era rewards builders who know how to make every GPU count. ⚡ On the Tech Talks Daily podcast, DDN’s Alex Bouzari shares how DDN’s focus on first principles has helped power more than 1 million GPUs worldwide while staying profitable for more than a decade. He explains why lasting AI Infrastructure must deliver customer value through real-world constraints like GPU availability, power limits, and supply volatility. Tune in to learn how customer-focused design can create stronger business outcomes in the AI era → bit.ly/4dzz5ax

Your GPUs should be accelerating AI, not recomputing context 🔄 In this demo, Barak Epstein, Product Manager at Google Cloud, shows how Managed Lustre can be used as a KV cache for inferencing. By saving context outside GPU or TPU memory, teams can retrieve precomputed context, reduce recomputation, and improve accelerator efficiency for large-context AI workloads. Learn how DDN and Google Cloud are helping teams get more performance and better value from AI Infrastructure 👇

LUG 2026 was all about performance, community, and what’s next for Lustre. 👏 DDN joined the Lustre community in Indianapolis for a week of conversations around next-gen HPC, AI infrastructure, and the data performance needed to keep modern workloads moving. Thanks to everyone who stopped by, joined the discussions, and made the week a success! #LUG2026

DDN’s Wendy Stusrud and ✨Amanda R. Lee✨ have been named to CRN’s 2026 Women of the Channel list! 🏅 The CRN Women of the Channel award recognizes standout women leaders across the IT channel, including vendors, distributors, solution providers, and partner-focused organizations. For DDN, this recognition highlights the impact Wendy Stusrud and Amanda Lee are making through channel strategy, partner enablement, brand leadership, and AI Infrastructure growth. It also reinforces DDN’s commitment to helping partners and customers succeed as AI adoption accelerates. Join us in congratulating Wendy and Amanda 👏

From proof of concept to production in hours, not months ⚡ In this video, Jason Brown, Senior Director of Product and Solutions Marketing at DDN, shares how the DDN Enterprise AI HyperPOD, built with Supermicro and accelerated by NVIDIA, helps organizations deploy AI Infrastructure that is pre-validated, turnkey, and ready for production. He breaks down how DDN Infinia, NVIDIA AI Enterprise software, and high-density compute come together to support RAG and inference with more than 90% GPU utilization, up to 10x power and cooling savings, 22x faster RAG pipelines, and 18x faster inferencing. Watch the video to see how DDN, Supermicro, and NVIDIA are helping enterprises move from concept to production faster with AI Infrastructure built to scale.

We're thrilled to share that DDN has been recognized in the Award-Winning Products category of the 2026 Artificial Intelligence Excellence Awards. 🏆 This recognition reinforces what we’ve believed all along: breakthrough AI outcomes depend on a data platform built for performance, scale, and real-world impact. Thank you to the Business Intelligence Group for the honor — and congratulations to the entire DDN team behind it. 👏

The GPUs may be the engines of AI factories, but the data layer decides whether they run at full speed or sit idle. 💪 Join DDN and NVIDIA at #NVIDIAGTC for a deep dive into the architecture powering next-generation AI infrastructure. 🎤 Unlocking Data at Scale for AI Factories with NVIDIA & DDN 🗓️ 9:00–9:40 AM Hear from: • James Coomer, SVP of Products, DDN • Jacob Liberman, Director, Enterprise Product, NVIDIA In this session, they’ll break down how data architecture built on the NVIDIA AI Data Platform reference design drives GPU efficiency, reduces energy and cooling demands, and enables high-performance RAG and multi-modal AI workloads. If you’re building or operating an AI factory, this conversation will highlight the design patterns, and pitfalls, that determine whether your AI infrastructure scales or stalls. 🎟️ Add this session to your GTC Schedule: bit.ly/4ltN0B5

What does “data movement” actually mean in AI? DDN's James Coomer explains how, in most real-world AI environments, GPU performance gets constrained by how fast data can move in and out during every phase: preparing datasets, training models, and running inference. He breaks down how massive AI supercomputers with thousands of GPUs still depend on nonstop data feeds, plus frequent model checkpointing to track progress and recover quickly if anything goes wrong. Watch the full interview to hear how eliminating data movement friction can unlock more GPU productivity and faster model timelines: bit.ly/4cbNSrB

Your EXAScaler is AI-ready. Join us to learn how to unlock it. 🔐 In this recent webinar, DDN's Joel Kaufman and Stephanie Giard break down what KV Cache actually is, why it matters, and how it impacts real-world performance as teams move from training → inference → agentic AI. Watch the replay: bit.ly/4aU60oG #Webinar

Watch as Kevin Cochrane, CMO at Vultr, shares how Vultr’s partnership with DDN drives 30x faster data delivery to training clusters and 15x better power efficiency across their AI Infrastructure. Learn how Vultr and DDN architect for scale and efficiency, and learn how you can accelerate your own large training workloads. ⬇️ Watch the full video here: bit.ly/49N4l3N

If you're running large AI workloads, this session could change your infrastructure strategy. 👇 Join Joel Kaufman (Senior Product Manager, DDN) and Peter Bojanic (Principal Customer Solutions Architect, DDN) for a live #webinar exploring how to enable and optimize KV Cache on EXAScaler. This session is focused on practical enablement and operational considerations, building directly on the KV Cache demo video. Reserve your spot now: bit.ly/4kjhpS3

65% of AI projects stall from skills gaps. Ready to join the 35% that succeed? A new survey of 600 IT and business leaders, conducted in collaboration with Cognizant and Google Cloud, shows how top organizations scale AI smarter, not just bigger. Get the full report to learn the architectures and practices that drive success: bit.ly/4pYJmQx

DDN is headed to the @wef in Davos! ✈️ Our President and Co-founder, Paul Bloch, will join “Beyond the Hype: Delivering the AI Intelligence Factory,” a session moderated by @McKinsey, alongside leaders from @NVIDIA and Aleria. The discussion will focus on what it takes to move from AI hype to execution, including real-world impact, strategic adoption, and tangible value creation at scale. #WEF26