GoKawiilLast week at Computex 2026, Wiwynn showed off one of the industry's first Nvidia SCADA (SCaled Accelerated Data Access) servers. Devices such as this are built to handle the extreme data demands of AI data center-focused inference and training workloads, which operate with massive models and datasets, therefore requiring large, fast, and connected devices to serve as the backbone for complex, high-throughput tasks that AI workloads depend upon.
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 I/O performance. The machine is based on Nvidia's Vera CPU, four RTX Pro 6000 Blackwell graphics cards, four PCIe 6.x switches, and four ConnectX-9 SuperNIC cards.
Storage architecture for AI
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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 I/O cannot efficiently handle such workloads and creates bottlenecks because the CPU must issue commands, manage requests, and control data transfers. Even in advanced solutions like GPUDirect Storage, which allows data to be transferred directly from SSDs to GPUs, the CPU still owns the control path and can become a bottleneck.
(Image credit: Tom's Hardware)
The SCADA platform, previewed in late 2025, is designed to allow GPUs access to very large datasets directly and efficiently without involving a central processor. This is impossible to do on conventional machines, as SCADA lets GPUs themselves initiate and control storage I/O operations and the data path.
(Image credit: Tom's Hardware)
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