如果您希望可以时常见面，欢迎标星收藏哦~ 来源： 内容编译自 eletimes 。 半导体行业正面临着复杂的挑战。设计一款现代芯片需要数十亿个晶体管、大量的验证工作量以及 易受干扰的全球供应链，这使得整个过程变得举步维艰。阻碍创新和市场响应的关键因素之一是漫 长的交付周期，通常超过20周。虽然采购和供应链经理需要不断协调晶圆厂、管理库存并应对快 速变化的市场，但该行业的核心瓶颈在于设计阶段的复杂性和迭代性。 包括大型语言模型 (LLM) 和新型多智能体生成系统在内的人工智能技术正在从根本上改变电子设 计自动化 (EDA)。这些系统可以自动生成寄存器传输级 (RTL)，更早地检测验证错误，并帮助预 测晶圆厂的计划。将人工智能与采购团队和供应链规划人员相结合，有助于应对行业波动和资源配 置的不确定性。它正在悄然重塑整个生态系统，将设计从依赖小型专家团队的艺术形式转变为计算 优化的流程。 人工智能在芯片设计自动化中的作用 RTL 设计定义了芯片的逻辑，传统上是手工完成的，需要工程师耗费数月时间进行调试。现在， 基于大型 HDL 数据集训练的 AI 可以识别 RTL 碎片，加速设计探索，并标记出不一致之处。强 化学习 ...

Core Viewpoint - The company Huada Jiutian (301269.SZ) has signed a strategic cooperation agreement with Moore Threads for 2024, focusing on key areas such as chip design automation and GPU technology innovation [1] Group 1: Strategic Cooperation - The strategic cooperation will involve collaboration on chip design automation, rapid iteration of digital and analog circuit design processes, and the promotion of domestic EDA tools [1] - The partnership aims to enhance the rapid evolution and innovation of GPU technology [1] - Current technical and business collaboration is progressing steadily [1]

Core Viewpoint - Governments worldwide are increasing investments in chip design tools and related research, creating new opportunities for startups and established EDA companies, highlighting the importance of design automation tools in domestic supply chains [2] Group 1: Investment Trends - There is a shift in funding focus from manufacturing to design, as the importance of design in the semiconductor industry is increasingly recognized [2][4] - The global AI race has pushed chip design beyond traditional limits, necessitating AI-driven tools to manage complex chip components and their interactions [2] - A shortage of engineering talent is creating gaps in design capabilities, which could lead to production issues in a competitive market [2] Group 2: Government and Private Sector Collaboration - Government interest in reshoring production is opening up more opportunities for private investment and collaboration on research funded by government initiatives [2][4] - The CHIPS Act is directing significant investments towards manufacturing and equipment, but there is a growing recognition of the need for investment in EDA [2][4] - Projects like Natcast aim to bridge the gap between long-term research and short-term industry needs by leveraging AI for RFIC design [4][6] Group 3: Role of Startups and Incubators - Startups are increasingly emerging from universities with strong electronic design programs, but they often struggle to secure sufficient seed funding to develop viable products [8] - Incubators are providing essential resources, including logistics, infrastructure, and access to foundries, enabling startups to achieve goals that were previously unattainable [8][9] - Collaborative efforts among established companies, startups, and universities are fostering innovation and accelerating the development of new technologies [4][8] Group 4: Funding Strategies - Successful funding strategies involve addressing broader industry challenges rather than focusing solely on EDA issues, which can attract more attention and investment [10][11] - Building networks and participating in public forums are crucial for young researchers and developers to gain visibility and secure funding [12][14] - The emergence of new funding models, such as the RAISe+ program in Hong Kong, encourages collaboration between government, industry, and academia [11][13]