Whitepapers

Explore how AI is redefining data center efficiency and scalability. Read Wiwynn’s latest white papers for strategies in cooling and cloud optimization.

White Paper: Introduction to SPDM Attestation between BMC and EROT on AI server

This whitepaper introduces SPDM attestation between a BMC and an External Root of Trust (EROT) on AI servers. It outlines SPDM prerequisites and the SPDM protocol flow. It then presents the system design, implementation guidance, and practical applications, followed by challenges and future...

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White Paper: Firmware Design for Hardware Partitioning

Hardware partitioning divides a single server into physically isolated subsystems with independent CPU, memory, and I/O resources—delivering fault containment, workload flexibility, and multi-tenant security beyond software virtualization.

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1 min read

White Paper: Rack Integration and Quality Assurance in Modern Data Centers

The evolution of modern data centers demands a shift from isolated hardware delivery to seamless infrastructure integration. This whitepaper introduces a structured, repeatable ODM-driven framework designed to bridge the critical gap between factory manufacturing and real-world data center...

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1 min read

White Paper: Advanced Microchannel Material - Diamond Composite Thermal Solutions

As AI and High-Performance Computing (HPC) push rack power densities beyond 250 kW and localized heat fluxes past the 500 W/cm² threshold, conventional copper and silicon cooling technologies are reaching their thermal limits. This whitepaper introduces a breakthrough in thermal management by...

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1 min read

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 combining NVIDIA SCADA (Scaled Accelerated Data Access) with a 100% liquid-cooled, fanless chassis housing 96 E3.S NVMe drives, we have created an...

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1 min read

White Paper: KV Cache Offload to Improve AI Inferencing Cost and Performance

This paper explores a disaggregated key-value (KV) storage architecture designed to efficiently offload KV cache tensors for generative AI workloads. By synergizing Wiwynn's OCP ORv3-compliant servers with Pliops' hardware-accelerated data path, this framework delivers a highly scalable and...

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1 min read

Autonomous AI Agent for End-to-End Component Data Extraction

This paper explores an advanced framework designed to automate the extraction of important attributes from unstructured part datasheets. By synergizing expert data science preprocessing with the Retrieval-Augmented Generation (RAG) architecture, we have achieved industry-leading recognition...

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White Paper: From Design to Live Operation: Wiwynn’s L12 AI Cluster Deployment with MLPerf Validation

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.

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1 min read

White Paper: AI Rack Management with Wiwynn UMS

This paper discusses the rapid expansion of AI workloads and the resulting transformation in data center infrastructure requirements. Traditional air-cooling systems are becoming less effective due to the increased power density of server racks. To address this challenge, the paper presents...

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