SK Hynix: AI Data Center Competition Shifts to Overall Infrastructure Architecture

SK Hynix stated that the competition in AI is shifting from the performance of individual chips to the design and operation of overall infrastructure architecture. The competitiveness of AI data centers relies on the seamless integration of five key elements: computing, memory, storage, networking, and power supply and cooling. The expansion of AI model scales has led to a surge in demand for computing power and data movement, with training requiring repeated access to massive datasets and inference relying on rapid retrieval of user request information, all of which impose higher demands on data center system architecture. At the memory level, HBM and server DRAM have formed a layered system to handle different bandwidth and capacity tasks. At the networking level, as large-scale training and inference depend on multi-server parallel processing, networking has become a critical factor determining the scalability of data centers. System design is transitioning from single-server to rack and cluster-level expansion. Omdia predicts that the AI data center chip market will grow from $123 billion in 2024 to $207 billion in 2025, reaching $286 billion by 2030. SK Hynix mentioned that Microsoft's Fairwater data center in Wisconsin spans about five football fields, indicating that infrastructure is being deployed on a larger scale, with memory becoming a key layer connecting computing and data.

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