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Video
September 9, 2026
Rethinking RAID for AI: Inside Graid Technology's GPU-Powered Storage
Identifying problems and solving them is part of daily life in IT. As SSD performance advanced, RAID architectures built for the hard drive era began falling behind — and eventually became the bottleneck. In this interview, Graid Technology CEO Leander Yu and VP of Product Development Alven Yen explain how the team rethought RAID from the ground up, moving core computation onto the GPU to eliminate the CPU bottleneck and unlock the full performance of NVMe SSDs.
The Problem: Traditional RAID Wasn't Built for This
"RAID technology has been around for a very long time, but it was originally designed for traditional hard drives," says Leander Yu, CEO. As SSDs caught up to — and now nearly match — the speed of the RAID controllers meant to manage them, funneling all that data through a single controller turned the controller itself into the bottleneck. Graid Technology's answer: move RAID processing off the controller entirely and onto the GPU's parallel architecture — GPU Accelerated Storage, applied to the RAID layer.
Moving RAID to the GPU: 10x the Performance
By offloading RAID computation to the GPU, Graid Technology's next-generation storage solution delivers over 300Gb/s of throughput and 36 million IOPS on a single server — more than 10 times the performance of the highest-end traditional RAID controllers on the market today. Data moves directly from SSD to operating system or application, with no controller in the way.
Extending the Platform: Intel VROC and the Edge
With the addition of the Intel VROC product line, Graid Technology's reach now extends well beyond high-performance computing. "With Intel VROC, we're able to provide an all-in-one complete solution, covering everything from compact IoT devices to edge systems," Yu explains — taking GPU-accelerated storage from the data center to IoT and edge computing deployments.
Enterprise-Grade Resilience, Without the Performance Trade-Off
Speed alone isn't the mission. "The primary purpose of RAID is to maintain redundancy," notes Alven Yen, VP of Product Development — ensuring an SSD failure never interrupts a business-critical service. Beyond standard RAID protection, Graid Technology's proprietary Distributed Journaling technology ensures data written to the array stays consistent and correct regardless of drive health, paired with real-time data recovery that continuously monitors SSDs for corruption and instantly restores data using redundancy the moment it's detected.
The Vision: Storage as Critical AI Infrastructure
As GPU performance accelerates and AI workloads — from large language models to high-performance computing — redefine what enterprises need from storage, speed alone is no longer enough. "Our goal is to deliver the highest level of data protection and business continuity without compromising storage performance," says Yu. It's a vision the whole team is building toward: making Graid Technology's GPU-accelerated, enterprise-resilient storage a foundational layer of AI infrastructure everywhere.
By The Numbers
- 10x the performance of the highest-end traditional RAID controllers
- 300Gb/s throughput on a single server
- 36 million IOPS on a single server
Ready to eliminate your storage bottleneck? Contact our team to see GPU Accelerated Storage in action.
News & Resources
September 14, 2026
Breaking the KV Cache Inference Wall — Solidigm Data Insights Podcast, Featuring Graid Technology
"You've got a four-lane highway, and to get to your storage, you have to go down to a one-lane bridge." Garrett McKibben joins Solidigm on TechArena's Data Insights podcast to unpack why KV cache overflow is choking AI inference.
Graid Technology CEO Leander Yu and VP of Product Development Alven Yen explain how moving RAID processing onto the GPU breaks the bottleneck traditional controllers cannot solve, delivering 36 million GPU-initiated IOPS for AI infrastructure.
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Join Graid Technology at Dell Technologies Forum Taipei 2026 and discover how SupremeRAID™ AE transforms local NVMe storage into a high-performance, scalable, and protected extended KV cache—reducing redundant computation and accelerating time to first token (TTFT).