【华泰证券：DeepSeek有望加速模型训练与CUDA解耦】金十数据2月21日讯，华泰证券研究认为，DeepSeek在V3中使用了相比CUDA更底层的PTX 来优化硬件算法，PTX是CUDA编译的中间代码，在CUDA和最终机器码之间起到桥梁作用。而NSA则使用了OpenAl提出的Triton编程语言高效编写GPU代码，Triton的底层可调用CUDA，也可调用其他GPU语言，包括AMD的rocm以及国产算力芯片语言，如寒武纪的思元590芯片和海光信息的深算一号（DCU）内置的HYGON ISA指令集。LLM的训练短期内虽未完全脱离CUDA 生态，但DeepSeek NSA的推出使其初步呈现出与CUDA解耦的趋势，并为后续适配更多类型的算力芯片奠定基础。以异腾为代表的国产算力已经很好的适配了DeepSeek-R1 等国产模型，并取得了高效推理的效果，华泰证券认为，伴随海外算力的受限，针对国产算力的优化或将有持续进展，值得重视。
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