Core Viewpoint - The article discusses Huawei's recent announcement regarding the open-source of its Ascend CANN software, which aims to lower the barriers for AI tool development and foster a new AI computing ecosystem [2][30]. Group 1: CANN Open Source and Developer Empowerment - CANN, which stands for Compute Architecture for Neural Networks, serves as a bridge between AI training frameworks and underlying AI chips, allowing developers to utilize computing power without needing to understand chip details [2][5]. - The open-source nature of CANN has garnered significant attention in the industry, as it empowers developers to define computing capabilities and customize their AI models [2][6]. - CANN supports seamless integration with major AI frameworks such as PyTorch, TensorFlow, MindSpore, and PaddlePaddle, enhancing developer flexibility [5][6]. Group 2: Development Paths Offered by CANN - CANN provides three development paths for different types of developers: 1. For those familiar with Python, CANN integrates with the Triton ecosystem, allowing easy migration of existing code [9]. 2. For system-level programmers seeking high performance, Ascend C offers low-level resource management capabilities [10]. 3. For developers looking for ease of use, the CATLASS operator template library simplifies the creation of matrix multiplication operators [11][13]. - The MLAPO fusion operator, part of the CATLASS library, significantly reduces computation time and enhances performance in large models [15]. Group 3: Architectural Innovations - CANN's architecture features a layered decoupling approach, allowing independent evolution of components, which reduces integration complexity for developers [21][22]. - The decoupling enables developers to selectively upgrade specific components based on their needs, facilitating easier customization and integration [23][29]. - CANN has transitioned from a monolithic software structure to a modular one, with independent components for various functionalities, enhancing flexibility and performance [24][26]. Group 4: Open Source Community and Growth - The open-source initiative of CANN is actively progressing, with over 27 sub-projects and a total of more than 3,700 stars on its repositories [35]. - The community-driven approach invites developers to contribute, thereby expanding the ecosystem and enhancing the technology's value through collaborative efforts [31][32]. - CANN's repositories include a variety of core libraries and tools, providing developers with ready-to-use resources for AI application development [16][36].

Core Viewpoint - The article discusses the transformation of the AI industry, emphasizing that the competition has shifted from hardware capabilities to a battle for software, developers, and ecosystem building, with Huawei's Ascend and its heterogeneous computing architecture CANN at the forefront of this change [1][4]. Summary by Sections CANN Open Source Announcement - Huawei's rotating chairman Xu Zhijun announced that the CANN hardware enabling will be fully open-sourced by December 30, 2025 [2]. Significance of CANN Open Source - The open-sourcing of CANN represents a profound self-revolution in the domestic AI infrastructure, aiming to break the closed model traditionally dominated by hardware manufacturers and embrace a more open and community-driven future [4][19]. - The success of the ecosystem relies on attracting academic innovation and creating a stable, universal, and efficient foundational tool for developers [5][18]. Developer Perspectives on CANN - Developers describe CANN's evolution as a challenging journey, with early versions requiring low-level programming skills, which hindered productivity [10][11]. - The introduction of the Ascend C programming language marked a significant improvement, aligning more closely with mainstream programming practices [15]. Challenges Faced by Developers - Early developers faced high technical barriers and a lack of stable architecture, leading to a difficult development environment [11][13]. - Systemic issues persisted, such as the inability to reproduce model accuracy across different frameworks due to a lack of transparency in the underlying systems [17]. The Role of Open Source - Open sourcing CANN is seen as a means to break down technical barriers and empower developers by providing transparency and control over the platform [21][23]. - The open-source model aims to foster a vibrant community where developers can contribute and innovate, moving away from reliance on a few official experts [29]. Ecosystem Empowerment - Open source provides unprecedented opportunities for deep integration between academia and industry, allowing researchers to address real-world problems and convert solutions into academic contributions [26]. - The shift from users to contributors is expected to cultivate a new generation of developers who can engage in high-quality projects [28]. Future Outlook for CANN - The current focus is on matching CUDA's capabilities while fostering original innovations within the CANN ecosystem [44]. - Huawei has committed to investing significant resources, including 1,500 petaflops of computing power and 30,000 development boards annually, to support the open-source community [45].