09/09/2024, 09:00 AM UTC
揭秘：“BBAT”万卡AI集群网络架构Unveiling the BBAT's AI Cluster Network Architecture
➀ 文章讨论了从千亿参数的语言模型到万亿参数的多模态模型的演变，这对于超万卡集群的底层计算能力提出了显著提升的需求。 ➁ 它描述了字节跳动、百度、阿里巴巴和腾讯的AI集群的网络架构，突出了Broadcom Tomahawk 5芯片、InfiniBand和RoCE等先进技术的使用。 ➂ 文章还深入探讨了百度的HPN-AIPod架构和阿里巴巴的HPN7网络，展示了它们高性能和可扩展的设计。➀ The article discusses the evolution of large models from billion-parameter language models to trillion-parameter multimodal models, necessitating a significant boost in underlying computing capabilities for ultra-thousand-card clusters. ➁ It describes the network architecture of ByteDance, Baidu, Alibaba, and Tencent's AI clusters, highlighting the use of advanced technologies like Broadcom Tomahawk 5 chips, InfiniBand, and RoCE. ➂ The article also delves into the innovative HPN-AIPod architecture of Baidu and Alibaba's HPN7 network, showcasing their high-performance and scalable designs.
---
本文由大语言模型（LLM）生成，旨在为读者提供半导体新闻内容的知识扩展（Beta）。
