The final thing that was just announced at GTC is our hyper pod solution. So our hyper pod solution is a core data center building block. So it is something where the GPU servers and the storage servers are integrated and delivered at different scaling sizes.So basically t-shirt sizing that you can get from super micro that's a combination of DDN storage infinia storage a cluster of GPUs and this is and this is available in t-arch sizing so that you could go from four GPU servers to 32 GPU servers and we wo ...

Company Growth & Strategy - Super Micro has experienced significant growth, evolving from a sub $1 billion company to a much larger entity due to the rise of AI [1] - Super Micro differentiates itself from tier one vendors by being 100% software-defined, aligning with the trend of startups in the server and storage industries [4] - Super Micro utilizes a building block approach, integrating from motherboard to rack level, and now data center building blocks for AI solutions [5][6][7] Product & Technology Focus - Super Micro offers a diverse storage server portfolio, including large capacity 3.5" drives and high-performance flash storage solutions [9][10] - Super Micro is developing advanced cooling solutions like DLC2, using warm water to improve power efficiency for high TDP components [13] - Super Micro emphasizes the importance of proper cabling and integration for delivering optimal performance at scale, addressing challenges with building block solutions [11][12] Partnership with DDN - Super Micro partners with DDN to deliver solutions, reselling DDN's Exoscale for traditional HPC and integrating with DDN's Infinia platform, a software-defined solution [14][15] - Super Micro and DDN have a strong relationship, cemented by a large AI cluster project [7] - Super Micro and DDN offer a hyper-pod solution, a core data center building block with integrated GPU and Infinia storage, available in various sizes from 4 to 32 GPU servers [16][17]

Hey everybody, Ethan Sloan with SanDisk. We're going to talk a little bit about SanDisk DDN powering the next generation of AI and HBC. Nobody's talked AI here, so this will be the first one, right.Obviously, a little bit about me. So, at SanDisk, enterprise solid state drive representation, helping to fuel the uh the channel. So the goal today is to answer questions with regards to who, what, where, why, when, and how.The who part is who am I. Ethan just introduced myself. Let's get into the what.Right. So ...

The key to unlocking AI and high performance computing success is data. But as organizations globally raise their AI and HPC ambitions, they are learning that implementing the right data strategy is easier said than done. These challenges can prevent a proof of concept from translating into a successful production grade deployment.Many of the most pressing data related issues come down to some fundamental challenges within the storage infrastructure. Put simply, AI scale workloads require AI scale storage. ...

Hey everybody, Ethan Sloan with SanDisk. We're going to talk a little bit about SanDisk DDN powering the next generation of AI and HBC. Nobody's talked AI here, so this will be the first one, right.Obviously, a little bit about me. So, at SanDisk, enterprise solid state drive representation, helping to fuel the uh the channel. So the goal today is to answer questions with regards to who, what, where, why, when, and how.The who part is who am I. Ethan just introduced myself. Let's get into the what.Right. So ...

Partner power is fueling the next leap in AI Infrastructure. Doug Cook, VP of Global Alliances, Partnerships and Sales at DDN, outlines how GSIs, resellers, OEMs, NCPs and hyperscalers working together are elevating DDN and customers. He highlights how a customer driven approach with partners turns ambitious goals into real outcomes. Watch to see how to plug into DDN’s partner ecosystem, accelerate go to market, and help customers scale AI faster. ...

AI token factories collapse without data intelligence. DDN can help. Here's the business problem.Most AI token factories fail not because of GPUs, but because data becomes a bottleneck. Token cost skyrocket. Power goes through the roof.Time to revenue stalls. And here's the NCP reality for cloud. Profitability isn't about selling GPU hours.It's about lowering token cost. DDN does that across training, inference, and rack at the system level, helping NCPs attract more customers. GPUs create power.DDN turns t ...

And every time the memory bandwidth gets big and the data demands get bigger. And so the bottlenecks [music] are when the GPUs are trying to run something but they're waiting for data in one way or the other. They're reading or writing.And if they're doing that, then they're wasting resources. They're wasting productivity at massive [music] scale. You know, when we talk about data center efficiency, um the new kind of phrase on everyone's lips [music] when they're building data centers is tokens for what.An ...

I'm the director for UFIT research computing and uh my team is sort of displayed there between the hyper computer system. Our function is to support AI and high performance computing from across the campus. So that's our our mission. That's what we spend all of our time.So let me briefly tell you the story. We started building Hypergr in 2012. We created a new data center and that's also when we really started our intense relationship with DDN.They've been with us all the way. The first version, first gener ...

Google Cloud Managed Luster Overview - Google Cloud Managed Luster is a fully managed service running on top of DDNX Scaler, launched 4 and a half months ago [1][7] - It addresses the need for high throughput and low latency storage in HPC environments to keep GPUs and CPUs efficiently fed with data [4][5] - The service is integrated with Google Cloud services like DCS and GKE, offering easy data import/export from/to Google Cloud Storage [7][8] Performance and Scalability - Google Cloud Managed Luster offers up to 1 TB (Terabyte) per second of throughput with sub-millisecond latency and millions of IOPS [9] - It scales from a starting size of 9 TB (Terabyte) up to 8 PB (Petabyte) [9] - Performance tiers range from 125 MB (Megabyte) per second per TB (Terabyte) to 1,000 MB (Megabyte) per second per TB (Terabyte), catering to different throughput needs [15] Customer Benefits and Use Cases - Customers have experienced significant performance improvements, with one customer, Resemble AI, achieving full GPU saturation and 6x faster performance compared to other storage solutions [10] - Sony Honda Mobility's department, Fila, saw a 3x performance improvement compared to their previous storage solution [17] - Key use cases include KV cache, multimodal training, and checkpointing, all requiring low latency and high throughput [11][13][14] Partnership with DDN - Google partnered with DDN (DataDirect Networks) due to their mature, reliable Exoscaler product with a rich feature set [6] - The partnership aims to provide a fully managed solution, relieving customers of storage management burdens [6]