证券代码：001287 证券简称：中电港 | | √特定对象调研 ☐分析师会议 | | --- | --- | | | ☐媒体采访 ☐业绩说明会 | | 投资者关系活动类别 | ☐新闻发布会 ☐路演活动 | | | ☐现场参观 | | | ☐其他（请文字说明其他活动内容） | | | 兴业基金 牟方晓 | | 活动参与人员 | 前海人寿保险 丁超凡 | | | 泽铭投资 单河 | | | 方正证券 金晶 | | 时间 | 2025年12月24日下午13:30-14:30 | | 地点 | 公司会议室 | | 形式 线下 | | | 上市公司接待人员姓名 | 证券事务代表 谢日增 | | | 投资者关系专员 邓丽婷 | | 交流内容及具体问答记录 | 首先向投资者介绍了公司所处行业情况、主要业务以及经营情 1、请问公司是英伟达产品的代理商吗？主要产品和应用领域 | | | 况，并就投资者关注的问题进行了交流，主要内容包括： | | | 是什么？ | | | 公司是英伟达的国内授权分销商之一，目前主要授权分销用于 | | | 数据中心的GPU、Jetson系列产品以及自动驾驶方面的汽车芯片等。 | | | 2、公 ...

Core Insights - The semiconductor industry is undergoing significant structural changes driven by the rise of edge generative AI, marking 2025 as the "Year of Edge Generative AI" [1] - The global edge AI chip market is projected to grow by 217% year-on-year in Q1 2025, outpacing the cloud AI chip market [1] - Different architectures such as GPU, NPU, and FPGA are evolving along distinct paths, reflecting varying technological philosophies among semiconductor companies regarding future computing paradigms [1] GPU Insights - General-purpose GPUs have excelled in AI applications due to their strong sparse computing capabilities and programmability [2] - Edge hardware must handle multiple tasks beyond single model inference, necessitating a global perspective in AI design [2] - Power efficiency (TOPS/W) will become more critical than absolute performance (TOPS) in future edge AI applications [2] - Imagination's E-series GPU IP has achieved a 400% performance increase to 200 TOPS with a 35% improvement in power efficiency [3] NPU Insights - NPUs are increasingly valuable in edge computing, addressing limitations of traditional processors like CPU and GPU in power consumption and latency [4] - NPUs excel in accelerating AI model inference, significantly improving execution efficiency in real-time applications such as object detection and voice recognition [4] - NXP's i.MX 95 series processor integrates an NPU with 2 TOPS, achieving a fourfold speed increase in image recognition tasks while reducing power consumption by 30% [4] FPGA Insights - FPGAs play a unique role in edge AI due to their reconfigurability and low-latency characteristics [5] - FPGAs can handle large data processing tasks, such as 8K video, more efficiently than CPUs and GPUs [5] - The development barriers for FPGAs are lowering, with vendors providing specialized IP modules and complete solutions [6] Vendor Strategies - Companies like STMicroelectronics and Renesas are combining MCU and NPU strategies to capture IoT market share [7] - Imagination is leveraging its GPU architecture to support complex automotive applications, while NVIDIA's Jetson series is popular among robot developers [7] - Altera focuses on data centers and edge inference markets, while Lattice targets low-power FPGA applications in smart cameras and sensors [8] M&A Activities - STMicroelectronics acquired DeepLite to enhance its AI algorithm optimization capabilities [9] - Qualcomm's acquisition of Edge Impulse aims to simplify AI development for edge devices [10] - NXP's acquisition of Kinara strengthens its position in high-performance AI inference for smart automotive and industrial applications [10] Conclusion - The semiconductor industry is experiencing profound changes driven by edge generative AI, with diverse architectures exploring future computing forms [11] - The evolution of technology is not linear but adaptive, requiring a combination of software and hardware advantages for efficient and flexible system solutions [11] - Companies are accelerating resource integration through mergers and acquisitions, enhancing their competitive edge in a rapidly changing market [11]