来源： 知合计算官微 未来，工作组还将搭建开放协作平台，培养开发者社区，汇聚产学研力量加速软硬件协同创新，并推动RISC- V在AI芯片领域的产业化应用，促进生态构建。 RISC-V与AI的融合已经成为RISC-V在高性能计算领域发展的核心技术趋势。 作为工作组组长单位，知合计算 已正式发布通推一体的"阿基米德"产品系列，通过在架构和产品层面实现RISC-V与AI的高效融合，加速打造 高性能计算领域的标杆产品。 关于知合计算 知合计算致力于开发基于RISC-V架构的高性能、可扩展"通推一体"CPU芯片，依托自身生态 优势，聚焦应用实际需求，以"应用定义产品"的方式，为包括通用人工智能在内的广泛应用场 景打造创新、高效的算力基础。 近日，人工智能产业工作委员会在中国国际供应链促进博览会期间成功举办"芯生万物·智合致远"全体成员大 会。 大会上，知合计算正式获授RISC-V人工智能技术融合工作组组长单位。 人工智能产业工作委员会由工信部指导成立，汇集国内AI产业链上下游企业与高校研究机构，立足技术、标 准、测试与生态，为产业合作、政企沟通提供平台。 下辖RISC-V人工智能技术融合工作组则旨在推动RISC-V在人 ...

Core Viewpoint - The article discusses the evolution of chip architectures, highlighting the rise of RISC-V as a new engine for transformation in the global chip industry, particularly in the context of AI and IoT, due to its open-source, simplified, and cost-effective nature [1][2]. Group 1: RISC-V's Current Status and Challenges - Despite the growing interest in RISC-V for high-performance applications, there is a lack of benchmark products that can compete with ARM and x86 architectures [2][3]. - The first-tier RISC-V products, such as SiFive's P870-D and others, still lag behind mainstream ARM and x86 offerings in terms of performance [2][3]. - The absence of high-performance RISC-V chips may hinder the development of a robust software ecosystem, as developers are less inclined to invest in a less popular architecture [2][3]. Group 2: Key Developments and Innovations - Knowledge Computing has introduced the "Archimedes" series of CPUs, which aim to integrate general computing and AI inference capabilities efficiently [6][15]. - The new RISC-V CPU core is positioned among the top-tier high-performance CPUs, capable of matching the performance of leading ARM and x86 products [7][14]. - The CPU core supports a wide range of RISC-V extensions and is designed to provide a complete software stack, including tools and operating systems, to facilitate easier adoption [9][12]. Group 3: Market Strategy and Ecosystem Development - Knowledge Computing is focusing on specific application scenarios, such as edge servers and AI model inference, to drive the adoption of RISC-V and build a more robust ecosystem [21][22]. - The company aims to establish benchmark products that can attract more developers and partners to participate in the RISC-V ecosystem, thereby enhancing market confidence [28][26]. - The strategy emphasizes collaboration over competition among domestic manufacturers to strengthen RISC-V's position in the global market and enhance its standard-setting capabilities [34][35].