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As AI server systems continue to scale rapidly in power and data throughput, cable density within server platforms has increased significantly. High-density cable designs introduce critical challenges, including signal integrity, assembly feasibility, and airflow efficiency, which become...
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As server power density continues to increase in modern AI and high-performance computing applications, direct liquid cooling (DLC) has become a critical thermal management solution for next-generation data centers.
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...
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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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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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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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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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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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...