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Nvidia's high-speed AI data center storage servers break cover, touting 2.9 petabytes of storage and extreme PCIe 6.0 performance

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Image accompanies the article at Tom's Hardware. No description was extracted from the source.

Last week at Computex 2026, Wiwynn showed off one of the industry's first Nvidia SCADA (SCaled Accelerated Data Access) servers.

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Summary

Wiwynn's SCADA server packs up to 96 liquid-cooled solid-state drives and therefore offers petabytes of storage space using currently available E3.S drives, and massive the reporter/O performance. Modern AI inference and training workloads often deal with massive datasets that exceed the memory capacity of an AI accelerator's onboard memory, which is why AI applications need to access rapid storage. While AI training is typically dominated by large sequential transfers, AI inference workloads such as vector search, retrieval-augmented generation (RAG), graph analytics, and KV-cache retrieval often rely on fine-grained random accesses (that frequently involve data blocks smaller than 4KB) with extreme parallelism, as the system deals with thousands of GPU threads. Traditional CPU-centric the reporter/O cannot efficiently handle such workloads and creates bottlenecks because the CPU must issue commands, manage requests, and control data transfers.

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