arXiv Machine Learning July 28, 2026 By Zhihao Xu, Hao Zhong, Zeting Zhou, Yuhang Xu, Haoyu Tong, Wei Wang, Jinshan Chen, Keqiang He, Chong Zhu, Shengzhong Liu, Fan Wu, Guihai Chen

Gleam: Adaptive Network-Efficient CUDA API Remoting for Cross-Device GPU Sharing over LANs

Read the original on arXiv Machine Learning →

arXiv:2607. 23115v1 Announce Type: cross Abstract: This paper aims to enable computation- and communication-efficient GPU sharing across devices within local area networks (LANs), facilitating ubiquitous AI inference on heterogeneous personal devices.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.

arXiv AI

Aug 3

Topology-Aware Data Movement for Disaggregated GPU Inference

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Jul 7

Data Driven Optimization of GPU efficiency for Distributed LLM-Adapter Serving

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arXiv AI

Jul 23

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arXiv AI

Sep 15

mKernel: Fast Multi-GPU, Multi-Node Fused Kernels

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arXiv AI

Jun 2

Lodestar: An Online-Learning LLM Inference Router

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arXiv AI

Sep 10

A Measurement Study of LLM Inference Trade-offs Across Edge Continuum Hardware

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By Maysam Khatib, Moysis Symeonides, Demetris Trihinas, George Pallis, Marios D. Dikaiakos

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