比H20性价比更高的AI服务器

Core Viewpoint - NVIDIA is focusing on the development of the GH200 super chip, which integrates advanced Hopper GPU and Grace CPU, offering significant performance improvements and cost-effectiveness compared to previous models like H20 and H100 [2][3][10]. Group 1: Product Development and Features - The GH200 architecture allows for a dual-bandwidth communication of 900GB/s between CPU and GPU, significantly faster than traditional PCIe Gen5 connections [2][3]. - GH200 features a unified memory pool of up to 624GB, combining 144GB of HBM3e and 480GB of LPDDR5X, which is crucial for handling large-scale AI and HPC applications [9][10]. - The Grace CPU provides double the performance per watt compared to standard x86-64 platforms, with 72 Neoverse V2 Armv9 cores and support for high-bandwidth memory [3][10]. Group 2: Performance Comparison - GH200's AI computing power is approximately 3958 TFLOPS for FP8 and 1979 TFLOPS for FP16/BF16, matching the performance of H100 but outperforming H20 significantly [7][9]. - The memory bandwidth of GH200 is around 5 TB/s, compared to H100's 3.35 TB/s and H20's 4.0 TB/s, showcasing its superior data handling capabilities [7][9]. - GH200's NVLink-C2C interconnect technology allows for a more efficient data transfer compared to H20, which has reduced bandwidth capabilities [9][10]. Group 3: Market Positioning and Pricing - GH200 is positioned for future AI applications, targeting exascale computing and large-scale models, while H100 serves as the current industry standard for AI training and inference [10]. - The market price for a two-card GH200 server is around 1 million, while an eight-card H100 server is approximately 2.2 million, indicating a cost advantage for GH200 in large-scale deployments [10]. - GH200 is designed for high-performance tasks requiring tight CPU-GPU collaboration, making it suitable for applications like large-scale recommendation systems and generative AI [10].