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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...
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Press
Updated on October 15, 2025
AI clusters using next-generation accelerators (e.g., NVIDIA GB200) push rack power density beyond 130 kW, making air cooling insufficient and driving adoption of direct liquid cooling (DLC). This whitepaper introduces Wiwynn’s Elastic Management Framework, a modular, scalable, interoperable architecture that unifies rack- and cluster-level monitoring and control across IT and facilities. The Wiwynn Universal Management System (UMS) enables autonomous rack-level protection and in-row CDU coordination, integrates heterogeneous sensors and controls via Redfish/Modbus/SNMP/analog/GPIO, and exports normalized telemetry to a Prometheus/Thanos platform with Grafana visualization and AlertManager response.
This paper first explains the Elastic Management Framework. It then details a production deployment showing faster leak isolation, safer power sequencing, and telemetry scaling to hundreds of endpoints. It presents lessons on IT/OT protocol standardization, modular rollout from rack to POD to data center, and joint IT–OT design for networking, security, data synchronization, and leak workflows to guide reliable, scalable operations.
Explore how Wiwynn’s Elastic Management Framework empowers AI data centers to achieve seamless orchestration from rack to facility. Download the full white paper to uncover strategies for managing high-density GPU clusters with advanced liquid cooling and intelligent infrastructure control.
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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...