How the future of data storage is evolving with strong GPUs and AI - SiliconANGLE (2024)

The future of the storage industry lies in infrastructure that is graphics processing unit and artificial intelligence capable, with companies looking to revolutionize the market by addressing the evolving storage needs of customers with innovative data platforms.

Current storage frameworks present challenges, such as practitioner gridlock, a skills gap and the need to reinvent infrastructure for AI, with no clear guidance on how to move data to AI and transform, according to Vaughn Stewart (pictured), vice president of systems engineering at Vast Data Inc. Vast Data aims to address the industry challenge of choosing between highly performant storage and low-cost, large-scale storage capacity.

“[Our founders] had a really good vision about looking up and saying, ‘Is AI a standalone process? Or is really the notion of AI or, maybe more importantly, accelerated computing, whether it’s GPU, TPU, IPU, is this the next wave of the future?” Stewart said. “That’s kind of where I think we’re very different than the storage industry and why we’re more a data platform than a storage array. Because what we believe is that you’re going to have accelerated computing all throughout your infrastructure.”

Stewart spoke with theCUBE industry analysts John Furrier and Lisa Martin at SC23, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed how companies, including Vast Data, are revolutionizing the market by addressing the evolving storage needs of customers with innovative data platforms. (* Disclosure below.)

Tier-two clouds emerging

New tier-two clouds are emerging, offering a more affordable and agile model for specialized environments enabled by semiconductors and partnerships with research institutions, according to Stewart.Organizations need large storage capacity with HPC performance, enterprise-grade resiliency, secure multi-tenancy, data encryption, quality of service, global namespace and the ability to burst into the cloud.

“If you look at Lambda, the number of research institutions that are their customers — whether you want bare metal or virtual machines so you can do dedicated or shared infrastructure — their costs are significantly lower than the hyperscalers,” Stewart said. “We’ve got partnerships with all of these vendors and engineering efforts that are in tow with all of them. But they’ve found their niche, which is to go and address this market in a more agile and more affordable model.”

The integration of AI into HPC validates previous methods, Stewart explained. It opens up new paths for commercialization, leading to a radical disruption in data management with a shift toward AI-driven governance and storage decisions. In essence, this means that the simplification of computing platforms is driving the adoption of AI and GPU-enabled infrastructure, he added.

“You can see where there’s a seismic delta between HPC systems that are fast but boutique and fragile and enterprise storage, which is robust and available and online, but not performing enough to meet the needs of accelerated computing,” Stewart said. “You sit down with the founders of a company who are like, ‘We’ve identified this.’ First is to solve the performance cost scale challenge. Next is to go and start to fold in all these data services, data processing platforms to give a more richer set of leveraging your data, reducing time windows, reducing moving data around, reducing cost.”

Here’s the complete video interview, part of SiliconANGLE’s and theCUBE’s coverage of SC23:

(* Disclosure: TheCUBE is a paid media partner for SC23. Neither Dell Technologies Inc., the main sponsor of theCUBE’s event coverage, nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE