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Events
May 26, 2026
Join Us at Interop Japan 2026
As AI models continue to scale, GPU memory and storage performance are becoming critical challenges in modern inference infrastructure.
KV cache offload to NVMe is no longer optional for many production AI environments — but without the right storage architecture, it can introduce additional latency, bottlenecks, and performance instability.
That’s where SupremeRAID™ AE and SupremeRAID™ HE come in.
SupremeRAID™ AE is designed for AI and GPU servers, enabling high-performance KV cache offload to local NVMe with near-native NVMe performance and enterprise-grade data protection.
SupremeRAID™ HE extends this performance to AI data centers and HPC clusters, delivering high-availability RAID for shared NVMe storage environments while supporting scalable, resilient infrastructure for large-scale AI workloads.
Together, SupremeRAID™ AE and HE help AI infrastructure overcome storage bottlenecks — from single GPU servers to rack-scale AI deployments.
At Interop Japan（株）ナノオプト・メディア 2026, we’re excited to showcase how Graid Technology enables high-performance, highly reliable AI storage for the next generation of inference infrastructure. See you in Tokyo! 🇯🇵🚀
📍 Booth 5U12-5 | June 10-12 | MAKUHARI MESSE, Tokyo
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.
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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).