智通财经网·2025-10-28 12:33Core Viewpoint - The report from Guotai Junan Securities highlights the challenges faced by large language models (LLMs) due to the "memory wall" issue, proposing SSD-based storage offloading technology as a new pathway for efficient AI model operation [1][2]. Industry Perspective and Investment Recommendations - The massive data generated by AI is straining global data center storage facilities, leading to a focus on SSDs as traditional Nearline HDDs face supply shortages. The industry is rated "overweight" [1][2]. - The growth of KV Cache capacity is surpassing the capabilities of High Bandwidth Memory (HBM), necessitating the optimization of computational efficiency and reduction of redundant calculations through KV Cache technology [2]. KV Cache Management and Technological Innovations - The industry is exploring tiered cache management technologies for KV Cache, with NVIDIA's Dynamo framework allowing for the offloading of KV Cache from GPU memory to CPU, SSD, and even network storage, addressing the memory bottleneck of large models [3]. - Samsung's proposal at the 2025 Open Data Center Conference suggests SSD-based storage offloading to enhance AI model performance, achieving significant reductions in token latency when KV Cache size exceeds HBM or DRAM capacity [3]. Market Dynamics and Supply Chain Adjustments - The demand for AI storage is driving a shift from HDDs to high-capacity Nearline SSDs, with NAND Flash suppliers accelerating production of ultra-large capacity SSDs (122TB and 245TB) in response to the supply gap in the HDD market [4].