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White Paper: GPU-Initiated, Liquid-Cooled, Ultra-High-Density Storage for Next-Gen AI
This paper introduces a paradigm shift in storage architecture designed to overcome the CPU-centric data path bottlenecks in modern AI workloads. By...
Press
Updated on December 31, 2025
Deploying large-scale AI clusters introduces engineering challenges that extend well beyond the individual server rack. From liquid cooling integration to high-voltage power distribution and network topology design, the "Last Mile" of AI infrastructure presents multifaceted integration complexities.
This paper outlines Wiwynn’s L12 deployment methodology for the NVIDIA GB200 NVL72 platform. Using our Elastic Management Framework and validating performance via MLPerf® Training v5.1, we demonstrate how a structured deployment approach ensures production readiness, minimizing risks and accelerating time-to-market for AI clouds.
See how Wiwynn’s L12 methodology and Elastic Management Framework streamline NVIDIA GB200 NVL72 deployment with MLPerf®-proven results. Download the white paper to navigate integration complexities and ensure Day-1 readiness.
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This paper introduces a paradigm shift in storage architecture designed to overcome the CPU-centric data path bottlenecks in modern AI workloads. By...
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This paper explores a disaggregated key-value (KV) storage architecture designed to efficiently offload KV cache tensors for generative AI workloads.
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This paper explores an advanced framework designed to automate the extraction of important attributes from unstructured part datasheets. By...