Cambricon(SH:688256) 半导体行业观察·2025-10-23 01:01Core Insights - The article discusses the rise of Cambricon, a leading AI chip company in China, highlighting its technological evolution and competitive edge against global giants like NVIDIA [5][26]. Group 1: Foundational Era - The inception of Cambricon is attributed to the academic journey of two brothers, Chen Yunji and Chen Tianshi, who laid the groundwork for deep learning processor architecture through their research at the Chinese Academy of Sciences [7]. - The "DianNao" series, introduced by the brothers, was one of the earliest systematic studies on deep learning processor architectures, addressing the efficiency bottlenecks of general-purpose CPUs/GPUs in executing neural networks [7][12]. Group 2: Technological Evolution - The article highlights ten significant papers published between 2014 and 2025, tracing the technological advancements from the "DianNao" architecture to the Cambricon series of AI chips [5]. - The first paper, "DianNao," demonstrated a high-throughput accelerator capable of executing 452 GOP/s with a power consumption of 485 milliwatts, achieving a speedup of 117.87 times compared to a 128-bit 2GHz SIMD processor [11]. - Subsequent innovations, such as "DaDianNao" and "PuDianNao," showcased significant performance improvements, with "DaDianNao" achieving a 450.65 times speedup over GPUs and "PuDianNao" supporting seven mainstream machine learning algorithms [14][20]. Group 3: Commercialization and Ecosystem Development - Cambricon's transition from academic research to commercial products was marked by the introduction of the "Cambricon ISA," a specialized instruction set for deep learning, which decoupled upper applications from lower hardware [26][30]. - The integration of Cambricon-1A into Huawei's Kirin 970 chip marked a significant commercial breakthrough, establishing Cambricon as a key player in the mobile AI chip market [37]. - Following the loss of Huawei as a major client, Cambricon pivoted to focus on its "Siyuan" (MLU) cloud chips and the NeuWare software platform, aiming to compete with NVIDIA's ecosystem [37]. Group 4: Future Challenges and Opportunities - The article concludes by emphasizing the challenges Cambricon faces against NVIDIA's established technology and the need to carve out a unique path in the AI chip market [59]. - Despite the challenges, the growing demand for autonomous AI computing in China presents a significant opportunity for Cambricon to leverage its academic roots and build a robust developer ecosystem [59].