DDN's Core Focus - DDN positions itself as an enabler and accelerator of data-driven innovation across industries and use cases, akin to Nvidia's role in compute [5] - DDN emphasizes the importance of high-performance data, pivoting from high-performance computing to address the data needs of scientific discovery, business outcomes, and financial outcomes [3] - DDN aims to accelerate value and outcomes by feeding compute with data, irrespective of use case, whether it's in universities, government agencies, or organizations in various sectors [6] Challenges and Solutions - Organizations face challenges such as GPUs sitting idle (40%), power limitations, and fragmented hardware/software in AI data [10][11] - DDN claims to keep GPU utilization high (99% or even 999% in some cases), significantly lowering the cost per token (70% lower) and reducing power/cooling/data center footprint [11][12] - DDN addresses these challenges with solutions like Diate Core, AI Fasttrack, and AI Blueprint, designed to lower costs, accelerate AI adoption, and provide reference architectures for sovereign AI implementations [13][14][15] Product and Technology - Diate Core combines EXA and Infinia to provide a unified platform that lowers costs, accelerates checkpointing, and optimizes GPU utilization [13] - AI Fasttrack aims to simplify AI adoption for organizations seeking to achieve business, scientific, and financial outcomes [14] - DDN's architecture combines HPC scale, enterprise reliability, and AI-native speed [20] Partnerships and Ecosystem - DDN partners with cloud providers like Google (DDN WEP offering), OCI, and Corewave to enable distributed consumption and global enablement [8][9][19] - DDN collaborates with Nvidia, center, and Deloitte to develop and validate sovereign AI blueprints [19] - Nvidia is a partner and customer of DDN, with DDN technology deployed internally by Nvidia [8] Industry Applications - DDN solutions aim to deliver faster simulations and better fraud models for financial services, and faster screening for life sciences [23] - DDN enables AI factories to operate 24/7, ensuring continuous operation without interruption [24][25] - DDN optimizes its platform for specific industries and use cases, recognizing that requirements differ between financial services, academia, life sciences, and autonomous driving [28][29] Sovereign AI Blueprint - DDN is involved in large sovereign AI implementations globally, including in the US, Europe, Asia-Pacific, and the Middle East [15] - The sovereign AI blueprint provides a reference architecture for building successful AI implementations at high speed [15] - Yoda Shakti in India utilizes 8,000 B200 GPUs at 99% utilization with 40% power savings based on DDN's blueprint [19]

Performance Highlights - Workloads are supercharged to achieve data intelligence [1] - The technology offers fast and very flexible performance [1] - Sheer performance and amazing throughput at low latencies are provided [1] - Performance is described as earthshattering [1]

I'm Paul Mloud. I'm a product director at Super Micro and my responsibility is for storage products and I've been working with with DDN for a good number of years and I'm really excited about this new Infinia product and our HyperPod solution that we're jointly going together to market. I really think that this is going to provide all the bits and pieces that an enterprise needs to put together a solution for rag data flows.The performance is there, the scaling is there, and the integration with the AI data ...

You want me to. Welcome back everyone. I'm John Fer with The Cube.We are live here at supercomputing 2025. I'm here with Dave Volante, my co-host Jackie Magcguire, Savannah P. The whole team is here unpacking the wave of AI infrastructure that continues to accelerate the value uh to the enterprise and to large cloud hyperscalers and neoclouds.A lot of action happening. Alex Bazari here, CEO of DDN is back on the cube. Alex, great to see you as always. as always. Always a real pleasure.You guys uh continuing ...

As you probably know, AI is already redefining the world economy from financial services to healthcare to automotive, energy, manufacturing, public sector. We are really starting to see great new AI applications come and this is all in partnerships with Nvidia, our great partner who has been pushing us on the envelope of innovation. So what we are talking about here is yes we've been here for many years 27 years in fact but the last 10 years has been amazing in 2015 almost 10 years ago we were supercharging ...

DDN's Origin and Mission - DDN was founded approximately 25 years ago and has experienced tremendous growth since then [2] - Initially focused on delivering large-scale high-performance computing data infrastructure, DDN has shifted towards providing AI solutions for training, inferencing, and data intelligence at scale, particularly through its relationship with Nvidia [3] - DDN aims to ensure customer success by aligning with customer needs, which has contributed to its growth and resilience against competition [11][12] AI Infrastructure and Data Intelligence - The AI industry is moving beyond the test phase, with large foundational models driving demand for increased scale (10x to 100x) [5] - Data intelligence, encompassing access to global data and the ability to ingest, analyze, load, and simulate exabytes of data, is crucial for AI model effectiveness [7] - DDN provides the infrastructure and data intelligence necessary for efficient AI system deployment, complementing Nvidia's offerings and various software applications [9][10] - DDN enables efficient training and inferencing, delivering tokens at the lowest cost, which is essential for maximizing the value of GPU deployments [12] Sovereign AI and Enterprise Adoption - Many countries are implementing sovereign AI strategies to enhance government services, security, research, and development [14] - Enterprises are exploring AI use cases, but face challenges in prioritizing and implementing them effectively; simplification is needed for broader adoption in the next 12 to 18 months [16] Industry Impact - AI is impacting various verticals, including medical, manufacturing, autonomous vehicles, genomics, banking (high-frequency trading), space, defense, and social media [18] - The current state of AI adoption is comparable to the early days of the internet or railroads, indicating significant future growth potential [18]

Partnership & Collaboration - DDN and Sandisk have a multi-year partnership focused on delivering solutions for both AI and HPC customers [1][2] - The partnership emphasizes agility, flexibility, and collaboration, resulting in solutions that fit well with both DDN and Sandisk offerings [2] Product Development & Strategy - The company is launching a new ultra QLC product line in 2026, offering high capacity options ranging from 32TB to 256TB [3] - The new product line aims to address the high-density needs of emerging data centers and provide balanced performance for AI, HPC, and other workloads [3] Performance & Efficiency - Performance is defined not only by speeds and feeds but also by the overall operational efficiency of the solution [1][2] - Operational efficiency includes form factor perspective and density perspective [2]

GDN best partners in the world with Nvidia. All the best. ...

Product Overview - Exoscaler is positioned as a platform for HPC (High-Performance Computing) and AI [1] - The platform is designed for large-scale training [1] - Exoscaler supports multimodal training with a large number of GPUs, ranging from thousands to hundreds of thousands [2] Key Improvements - The company has focused on making Exoscaler easier to use, deploy, and upgrade over the past two years [2] - Exoscaler now features easy online updates [2] - Multi-tenancy has been improved, making Exoscaler fully multi-tenant ready, which is crucial for cloud environments [2]

So this year at supercomput was uh was was quite different and very interesting. You know traditionally I heard a lot about how computers are getting better and faster and bigger and more scaling that needs more cooling. But this year I saw a renewed energy around enabling additional supercomput capabilities through GPU acceleration.There's a lot of talk about how Nvidia can help uh supercomput including uh what DDN does for the for the world of HPC and AI in terms of enabling whether it's AI data platform ...