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English(EN) Halley: A Predictive Control Plane for Optical AI Data Center Networks

Halley框架提升AI数据中心光网络效率

一种名为Halley的新型预测性控制框架已被开发出来,旨在提高AI数据中心内光网络的效率。Halley可以预测激光器和光交换机等四个网络层的潜在故障,并实施具有正式保证的控制措施。模拟表明,在备用容量耗尽的情况下,Halley可以将有效吞吐量从65.2%显著提高到76.5%;在仅特定通道带宽损失的情况下,则可提高到67.4%。这种优化意味着每兆瓦的数据中心容量需求可能减少3.3%至14.7%。 AI

影响 通过提高网络吞吐量和降低容量需求来优化AI训练基础设施。

排序理由 该条目描述了一篇关于AI数据中心网络新框架的研究论文。[lever_c_demoted from research: ic=1 ai=0.7]

在 Hugging Face Daily Papers 阅读 →

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Halley框架提升AI数据中心光网络效率

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报道来源 [1]

  1. Hugging Face Daily Papers TIER_1 English(EN) ·

    Halley:面向光学AI数据中心网络的预测性控制平面

    Halley is a predictive control framework for AI data center optical networks that improves effective throughput and reduces capacity needs by forecasting failures and controlling resources with formal guarantees.