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新的X-Stage流水线优化提升DiT推理速度

研究人员发现了一个新的流水线阶段,称为X-Stage,可以优化扩散Transformer(DiT)推理过程中的通信-计算重叠。该阶段专注于通信启动后但尚未完全可见的期间,从而更好地预测和管理发送方背压。通过对这个X-Stage进行建模,研究人员重新设计了DeepGEMM MegaMoE和Ulysses序列并行注意力模型的通信-计算融合内核,与现有基线相比实现了显著的加速。 AI

影响 这项研究引入了一种新颖的优化技术,有望实现更大规模扩散模型的更快、更高效的推理。

排序理由 详细介绍AI模型推理新技术的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 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X-Stage流水线优化提升DiT推理速度

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详细介绍AI模型推理新技术的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Jianwen Xian, Zhiyuan Xu, Yuchen Li, Ziliang Lai, Kang He, Zhen Huang, Aichen Feng, Jinyan Chen, Yilin Zhang, Qinqin Chen, Chengru Song ·

    X-Stage:DiT推理中通信-计算重叠的被忽视的管道阶段

    arXiv:2607.23264v1 Announce Type: cross Abstract: Fine-grained, device-initiated communication lets persistent GPU kernels in distributed diffusion transformer (DiT) inference issue remote stores and overlap data movement with Tensor Core computation. Existing systems schedule wh…