DeepSeek突然拥抱国产GPU语言！TileLang对标CUDA替代Triton，华为昇腾Day0官宣支持适配

Core Viewpoint - The article highlights the significance of TileLang, a domain-specific language for GPU kernel development, which has been adopted by DeepSeek in its v3.2 update, showcasing its performance advantages over traditional methods like Flash Attention 2 [1][6][26]. Group 1: TileLang Overview - TileLang is designed to simplify the development of high-performance GPU/CPU kernels, comparable to NVIDIA's CUDA, and is recommended by DeepSeek for experiments due to its debugging and rapid iteration advantages [6][10]. - The language allows developers to write efficient code with significantly reduced lines, achieving performance parity with existing implementations [5][8]. - TileLang's development is led by a team from Peking University, including key figures such as Wang Lei and Dong Yuqi [15][19]. Group 2: DeepSeek's Adoption of TileLang - DeepSeek's choice to use TileLang was first showcased at the Beijing Zhiyuan Conference in June, where its potential for faster operator implementation was discussed [10][11]. - The integration of TileLang has been recognized by industry leaders, including Huawei, which announced support for the language [7][4]. - DeepSeek's v3.2 release demonstrates that TileLang can effectively be used for model training, validating its capabilities in real-world applications [34][26]. Group 3: Performance and Technical Aspects - TileLang provides three programming interfaces catering to different developer expertise levels, from beginners to performance-focused experts [20][21][23]. - The language's architecture allows for decoupling scheduling space from data flow, enabling more efficient optimization by the compiler [19]. - DeepSeek's implementation of TileLang has resulted in significant performance improvements, with claims of achieving a 30% speed increase over traditional methods [5][27].