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English(EN) Efficient Expert-Parallel Communication on PCIe-Connected Consumer GPUs

新的ThunderEP设计提升消费级GPU上的MoE推理性能

研究人员开发了ThunderEP,这是一种新的通信设计,用于在通过PCIe连接的消费级GPU上高效运行大型专家混合(MoE)模型。该系统解决了这些设置中固有的通信瓶颈,数据传输通常涉及CPU。ThunderEP旨在绕过CPU中继跳跃并利用DMA引擎,避免与计算资源的争用,从而减少同步延迟。在配备RTX 4090和RTX 5090 GPU的系统上进行的评估表明,与NCCL等现有方法相比,速度显著提升,MoE推理的端到端改进高达1.66倍。 AI

影响 优化消费级硬件上大型MoE模型的推理性能,可能降低研究人员和开发人员的门槛。

排序理由 该项目是一篇研究论文,详细介绍了一种在特定硬件上优化AI模型推理的新技术方法。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.LG 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

新的ThunderEP设计提升消费级GPU上的MoE推理性能

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该项目是一篇研究论文,详细介绍了一种在特定硬件上优化AI模型推理的新技术方法。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.LG TIER_1 English(EN) · Jaehwan Lee, Sangmin Lee, Chaewon Kim, Junsik Shin, Jaejin Lee ·

    PCIe连接消费级GPU上的高效专家并行通信

    arXiv:2609.40093v1 Announce Type: cross Abstract: Expert parallelism (EP) enables inference of large Mixture-of-Experts (MoE) models by placing their experts across multiple GPUs, but requires substantial communication between GPUs at every MoE layer. As contemporary MoE models a…