English(EN) Partition-Aware Scheduling for Mobile Heterogeneous Inference Co-Execution

新框架优化移动端AI推理延迟

作者 PulseAugur 编辑部 · [1 个来源] · 2026-09-15 04:00

研究人员开发了一种新的移动异构推理调度框架，结合了算子间和算子内并行。该方法旨在减少由静态有向无环图（DAG）表示的任务的推理延迟，例如涉及CNN或Vision Transformers的任务。提出的在线迭代搜索框架将大型DAG分解为多个阶段，并使用延迟预测器来估计分区执行，从而在部署时以最小的开销实现平台特定的调度。 AI

影响该框架可以显著降低移动设备上AI推理的延迟，从而能够更高效地运行更复杂的模型。

排序理由该集群包含一篇详细介绍AI推理新技术框架的研究论文。[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 →

本文如何被排名

Signal score: 15 / 100; Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket: Tool; 该集群包含一篇详细介绍AI推理新技术框架的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]
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Topics: paper, infra; Editorial topic classification. Feeds into how the story surfaces on /topic/<slug> hub pages and into the per-entity coverage mix.
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完整方法见我们的编辑标准。

报道来源 [1]

arXiv cs.LG TIER_1 English(EN) · Zhuojin Li, Marco Paolieri, Leana Golubchik · 2026-09-15 04:00

面向移动异构推理协同执行的感知分区调度

arXiv:2609.14213v1 Announce Type: cross Abstract: Modern mobile inference runs on heterogeneous platforms combining mobile GPUs with multiple CPU core clusters. Existing optimizations typically exploit either inter-operator parallelism, by assigning entire operators to CPU cores …

本文如何被排名

报道来源 [1]

面向移动异构推理协同执行的感知分区调度

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