Explore the cutting edge of computing from data center to edge including solutions unlocking the AI pipeline, all backed by Solidigm's leading SSD portfolio.

Supermicro has been a player in the tech industry for over 30 years, focusing on building breakthrough solutions for data center compute requirements. Their history as a nimble infrastructure supplier has driven them ahead as a leader in AI era compute delivery. This is why I was so excited to invite Supermicro’s Paul McLeod to the TechArena Data Insights podcast sponsored by Solidigm. My co-host Jeniece Wnorowski and I put Paul through his paces to discuss Supermicro’s perspective on AI era computing, what customers are demanding of infrastructure, and how the data pipeline is a central innovation focus for today’s deployment targets.
The changing landscape of data management in AI workloads
Paul started by discussing the history of data management across data center environments stating that traditionally, IT has involved infrastructure silos for specific storage needs, with limited data accessibility across storage solutions. Paul added that with AI this is changing. AI demands all these data types and pipeline workloads to function simultaneously. Supermicro utilizes this evolving requirement to deliver value to customers. Paul pointed out that Supermicro’s heritage includes early use of NVMe technology, giving them valuable experience in storage solutions for AI.
This has shaped by a flattening of the traditional tiered storage model. Previously, cold tiers existed for data that rarely needed to be accessed. However, with AI, fast access to almost all data has become critical meaning that the cold tier is heating up into warm tier storage where flash alternatives shine. For this transition, Supermicro's solutions have featured Solidigm’s D5P5430 SSDs. These SSDs were designed to solve the unique challenges of data center enviroments, including delivery of high-density storage high performance storage drives needed for AI training. The P5430, their premier QLC-based offering, is available in various form factors to accommodate different server designs and thermal requirements and delivering impressive capacity, reaching up to 30 terabytes. Paul noted that the technology was dialed in for Supermicro’s requirements highlighting that bottlenecks have shifted from storage to compute and network. This is made even better with key collaborations with storage partners taking advantage of underlying infrastructure to fuel even the most grueling customer requirements.
Looking ahead: The future of data storage for AI workloads
Where does the market take platform innovation next? Paul pointed out the need for continued innovation of the data pipeline to reach additional scale in performance, compute density and efficiency. As large language models scale and customers demand more compute to train algorithms, keeping the data pipeline in balance and fed with rely on continued industry collaborations with partners like VAST Data and Solidigm. Be sure to visit Supermicro and Solidigm’s websites for more information about storage and compute solutions for the AI era, and continue following the TechArena as we explore data insights.

TechArena host Allyson Klein and Solidigm’s Jeniece Wnorowski chat with Weka’s Joel Kaufman, as he tours the Weka data platform and how the company’s innovation provides sustainable data management that scales for the AI era.

TechArena host Allyson Klein is joined by Solidigm’s Jeniece Wnorowski as they continue to explore rapid data innovation fueling today’s computing. In today’s episode, they chat with VAST Data’s Global VP of Engineering, Subramanian Kartik, as he describes how his team has delivered a breakthrough data platform for the AI Era.

I recently attended NVIDIA GTC, called by some as the Woodstock moment of the AI Era, and I’m still unpacking what we learned there about industry innovation to fuel AI workloads. While the TechArena packed as many conversations possible with industry innovators at the event, one conversation that stood above the rest was our interview with CoreWeave’s Jacob Yundt. He leads infrastructure buildout for CoreWeave as they chart a trajectory for delivering unparalleled scale for AI training in the cloud.
How did they do it? As we have seen at many inflection points, CoreWeave took advantage of not being encumbered by legacy to deliver a cloud stack that was specially built for AI training clusters from initial provisioning to health checks, orchestration and scheduling. This enables the company to bring up a staggering amount of GPUs to a particular training task at warp speed while providing reliable compute throughout the training period. CoreWeave provides proactive oversight of its instances to ensure that precious training cycles are not disrupted based on potential hardware failures, I/O issues, or other maladies that confront data center infrastructure.
CoreWeave has developed a cult-like following amongst AI startups looking to train algorithms where speed to train often is the difference for market opportunity. Jacob clarified their market focus on any customer looking to do “ground-breaking work at incredible scale”, and this speaks to the type of underlying infrastructure requirements they have across compute, storage, and network. And the demand for this infrastructure is stark. CoreWeave has been on record stating that power demand alone from its training clusters may stress local power grids in the communities where it operates, and the demand for CoreWeave is also growing exponentially. Valued at $7B last December, the latest discussion of valuation of the company four months later has surged to $16B underscoring the growth potential for AI training.
So what infrastructure is CoreWeave tapping to deliver their AI service? It’s no secret that their training relies on NVIDIA GPUs, and CoreWeave will be integrating next generation Blackwell GPUs into clusters utilizing liquid cooling technologies. But Jacob stressed that there’s more than GPUs that goes into the groundbreaking scale they’ve been able to achieve. That scale starts with re-imagining the data pipeline, and CoreWeave has leaned into a strategic partnership with VAST Data to deliver innovative data management and control that scales with GPU performance needs. VAST Data’s platform has driven new capabilities for managing data sets to bring data more efficiently and quickly to the processing complex eliminating much of the overhead associated with traditional tiered storage solutions.
Jacob stated that the collaboration with VAST Data begins with his team’s love of QLC storage and the careful balance between performance, capacity and efficiency that QLC delivers. To say that Jacob is a fan of QLC is an understatement, and it’s no surprise given QLC’s advantages over TLC technology in delivering increased data density per cell. Jacob stated that his long-standing collaboration with Solidigm has ensured QLC deployment in his data centers with a partnership that extends beyond procurement to account and engineering support. When you consider the size of LLMs being trained at CoreWeave, it’s easy to guess that that’s a lot of QLC NAND being deployed.
So what’s next for CoreWeave? Watch this space to learn more about their continued infrastructure buildout as a harbinger of broader AI market adoption. I’m also interested to see if CoreWeave can make a dent in the cloud service provider landscape with their built for AI training stack. I’ll also be reporting on advances of the data pipeline infrastructure industry including in my Data Insights series with Solidigm.

TechArena hosts Allyson Klein and Jeniece Wnorowski chat with CoreWeave’s Jacob Yundt about how his organization is delivering a scalable data pipeline to AI customers utilizing breakthrough VAST Data solutions featuring Solidigm QLC SSDs.

TechArena kicks off a Data Insights Series in collaboration with Solidigm, and TechArena host welcomes co-host Jeniece Wronowski and Solidigm data center marketing director Ace Stryker to the program to talk about data in the AI era, the series objectives, and how SSD innovation sits at the foundation of a new data pipeline.

TechArena host Allyson Klein chats with Solidigm’s Roger Corell and Tahmid Rahman at the OCP Summit about their company’s heritage in the storage arena and how their SSD portfolio delivers the performance and efficiency required for the AI era.