Nvidia(US:NVDA) 3 6 Ke·2025-04-08 11:28Core Insights - NVIDIA is fully committed to making Python a first-class citizen in the CUDA parallel programming framework, marking a significant shift in its approach to GPU programming [1][4] - The company aims to enhance the developer experience by integrating native Python support into its CUDA toolkit, allowing developers to execute algorithmic computations directly on GPUs using Python [1][5] Group 1: Native Python Support - NVIDIA has announced that its CUDA toolkit will provide native support for Python, which has been lacking for many years, thus allowing developers to use Python for GPU programming without needing to learn C or C++ [1][2] - The year 2025 is designated by NVIDIA as the "Year of CUDA Python," indicating a strategic focus on integrating Python into its ecosystem [1][3] Group 2: Developer Ecosystem Expansion - NVIDIA is not abandoning C++ but is expanding its support for the Python community, significantly increasing its investment in this area [4][5] - The introduction of higher-level abstractions like CuTile and Python versions of libraries such as Cutlass allows developers to work in Python without needing to write C++ code, thus democratizing GPU programming [5][6] Group 3: Programming Model and Performance - The CuTile programming model is designed to align better with Python's characteristics, focusing on arrays rather than threads, which simplifies the coding process for developers [15][16] - NVIDIA emphasizes that the performance of GPU computations will remain high while making the code easier to understand and debug [16][17] Group 4: Strategic Vision - NVIDIA's overall vision is to provide a complete experience for Python developers within the CUDA ecosystem, ensuring seamless interoperability across various layers of the technology stack [3][9] - The company is actively recruiting programmers to support additional programming languages like Rust and Julia, indicating a broader strategy to enhance its development ecosystem [8]