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English(EN) GF-DiT: Scheduling Parallelism for Diffusion Transformer Serving

GF-DiT 通过动态并行优化 Diffusion Transformer 服务

研究人员开发了 GF-DiT,一个新颖的运行时系统,旨在优化 Diffusion Transformers (DiTs) 的服务,DiTs 越来越多地用于图像和视频生成。与使用静态并行性的现有系统不同,GF-DiT 根据工作负载需求和服务目标动态调整 GPU 并行性。这是通过异步执行抽象和称为 group-free collectives 的通信抽象实现的,从而能够有效地在线重新分配 GPU 并减少通信开销。 AI

影响 这项研究可以显著提高 AI 驱动的图像和视频生成服务的效率并降低延迟。

排序理由 该集群描述了一篇关于优化 AI 模型服务的新颖系统的研究论文。[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 →

GF-DiT 通过动态并行优化 Diffusion Transformer 服务

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该集群描述了一篇关于优化 AI 模型服务的新颖系统的研究论文。[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) · Minyi Guo ·

    GF-DiT:扩散 Transformer 服务调度并行性

    Diffusion Transformers (DiTs) have become the dominant architecture for image and video generation, creating growing demand for efficient DiT serving. Existing systems assign each request a fixed parallel configuration throughout its lifetime. However, DiT workloads exhibit subst…