Cover Image

ACE-GNN: Adaptive GNN Co-Inference with System-Aware Scheduling in Dynamic Edge Environments

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Zhou, Ao, Yang, Jianlei, Qiao, Tong, Qi, Yingjie, Wei, Xinming, Duan, Cenlin, Zhao, Weisheng, Hu, Chunming
Format:	Preprint
Published:	2025
Subjects:	Distributed, Parallel, and Cluster Computing
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Towards Affordable, Adaptive and Automatic GNN Training on CPU-GPU Heterogeneous Platforms
by: Qiao, Tong, et al.
Published: (2025)

GreenDyGNN: Runtime-Adaptive Energy-Efficient Communication for Distributed GNN Training
by: Niam, Arefin, et al.
Published: (2026)

DGNNFlow: A Streaming Dataflow Architecture for Real-Time Edge-based Dynamic GNN Inference in HL-LHC Trigger Systems
by: Maharaj, Davendra, et al.
Published: (2026)

Environment-Aware Dynamic Pruning for Pipelined Edge Inference
by: O'Quinn, Austin, et al.
Published: (2025)

RIPPLE++: An Incremental Framework for Efficient GNN Inference on Evolving Graphs
by: Naman, Pranjal, et al.
Published: (2026)

Ripple: Scalable Incremental GNN Inferencing on Large Streaming Graphs
by: Naman, Pranjal, et al.
Published: (2025)

HopGNN: Boosting Distributed GNN Training Efficiency via Feature-Centric Model Migration
by: Chen, Weijian, et al.
Published: (2024)

Many Hands Make Light Work: Accelerating Edge Inference via Multi-Client Collaborative Caching
by: Liang, Wenyi, et al.
Published: (2024)

Incremental GNN Embedding Computation on Streaming Graphs
by: Wang, Qiange, et al.
Published: (2026)

AcOrch: Accelerating Sampling-based GNN Training under CPU-NPU Heterogeneous Environments
by: Chen, Kefu, et al.
Published: (2026)

MSAO: Adaptive Modality Sparsity-Aware Offloading with Edge-Cloud Collaboration for Efficient Multimodal LLM Inference
by: Yang, Zheming, et al.
Published: (2026)

Adaptive Heuristics for Scheduling DNN Inferencing on Edge and Cloud for Personalized UAV Fleets
by: Raj, Suman, et al.
Published: (2024)

SneakPeek: Data-Aware Model Selection and Scheduling for Inference Serving on the Edge
by: Wolfrath, Joel, et al.
Published: (2025)

A Unified CPU-GPU Protocol for GNN Training
by: Lin, Yi-Chien, et al.
Published: (2024)

Deal: Distributed End-to-End GNN Inference for All Nodes
by: Chen, Shiyang, et al.
Published: (2025)

MoA-Off: Adaptive Heterogeneous Modality-Aware Offloading with Edge-Cloud Collaboration for Efficient Multimodal LLM Inference
by: Yang, Zheming, et al.
Published: (2025)

MSPipe: Efficient Temporal GNN Training via Staleness-Aware Pipeline
by: Sheng, Guangming, et al.
Published: (2024)

Understanding and Reducing Metadata-Driven Host Overheads in Sampling-Based GNN Training
by: Gong, Yidong, et al.
Published: (2026)

LSM-GNN: Large-scale Storage-based Multi-GPU GNN Training by Optimizing Data Transfer Scheme
by: Park, Jeongmin Brian, et al.
Published: (2024)

ACE-Sync: An Adaptive Cloud-Edge Synchronization Framework for Communication-Efficient Large-Scale Distributed Model Training
by: Yang, Yi, et al.
Published: (2025)

RapidGNN: Communication Efficient Large-Scale Distributed Training of Graph Neural Networks
by: Niam, Arefin, et al.
Published: (2025)

ARGO: An Auto-Tuning Runtime System for Scalable GNN Training on Multi-Core Processor
by: Lin, Yi-Chien, et al.
Published: (2024)

CondenseGraph: Communication-Efficient Distributed GNN Training via On-the-Fly Graph Condensation
by: Zhang, Zizhao, et al.
Published: (2026)

NeutronTP: Load-Balanced Distributed Full-Graph GNN Training with Tensor Parallelism
by: Ai, Xin, et al.
Published: (2024)

Preemption Aware Task Scheduling for Priority and Deadline Constrained DNN Inference Task Offloading in Homogeneous Mobile-Edge Networks
by: Cotter, Jamie, et al.
Published: (2025)

SLICE: SLO-Driven Scheduling for LLM Inference on Edge Computing Devices
by: Chow, Will
Published: (2025)

SLO-Aware Scheduling for Large Language Model Inferences
by: Huang, Jinqi, et al.
Published: (2025)

GriNNder: Breaking the Memory Capacity Wall in Full-Graph GNN Training with Storage Offloading
by: Song, Jaeyong, et al.
Published: (2026)

CoEdge-RAG: Optimizing Hierarchical Scheduling for Retrieval-Augmented LLMs in Collaborative Edge Computing
by: Hong, Guihang, et al.
Published: (2025)

Single-GPU GNN Systems: Traps and Pitfalls
by: Gong, Yidong, et al.
Published: (2024)

Arrow: Adaptive Scheduling Mechanisms for Disaggregated LLM Inference Architecture
by: Wu, Yu, et al.
Published: (2025)

SchEdge: A Dynamic, Multi-agent, and Scalable Scheduling Simulator for IoT Edge
by: Hamedi, Ali, et al.
Published: (2025)

Toward Sustainability-Aware LLM Inference on Edge Clusters
by: Rajashekar, Kolichala, et al.
Published: (2025)

Scaling Large-scale GNN Training to Thousands of Processors on CPU-based Supercomputers
by: Zhuang, Chen, et al.
Published: (2024)

Taming Request Imbalance: SLO-Aware Scheduling for Disaggregated LLM Inference
by: Wang, Qipeng
Published: (2026)

Adaptive Device-Edge Collaboration on DNN Inference in AIoT: A Digital Twin-Assisted Approach
by: Hu, Shisheng, et al.
Published: (2024)

OCTOPINF: Workload-Aware Inference Serving for Edge Video Analytics
by: Nguyen, Thanh-Tung, et al.
Published: (2025)

InkStream: Real-time GNN Inference on Streaming Graphs via Incremental Update
by: Wu, Dan, et al.
Published: (2023)

A Cloud-Based Spatio-Temporal GNN-Transformer Hybrid Model for Traffic Flow Forecasting with External Feature Integration
by: Zheng, Zhuo, et al.
Published: (2025)

GNNBENCH: Fair and Productive Benchmarking for Single-GPU GNN System
by: Gong, Yidong, et al.
Published: (2024)