论文解析:Insights into DeepSeek-V3: Scaling Challenges and Reflections on Hardware for AI Architectures
论文解析:Insights into DeepSeek-V3: Scaling Challenges and Reflections on Hardware for AI Architectures
大语言模型(LLMs)的快速规模化暴露了当前硬件架构在内存容量、计算效率、互联带宽的瓶颈。DeepSeek-V3通过硬件感知的模型协同设计,在2048块NVIDIA H800 GPU上实现了低成本大规模训练与推理。随着集群规模的指数级增长,硬件的鲁棒性与可靠性对于大模型将愈加重要。


