English

FlexPie: Accelerate Distributed Inference on Edge Devices with Flexible Combinatorial Optimization[Technical Report]

Distributed, Parallel, and Cluster Computing 2025-02-24 v1
Authors: Runhua Zhang , Hongxu Jiang , Jinkun Geng , Yuhang Ma , Chenhui Zhu , Haojie Wang
View on arXiv ↗ PDF ↗

Abstract

The rapid advancement of deep learning has catalyzed the development of novel IoT applications, which often deploy pre-trained deep neural network (DNN) models across multiple edge devices for collaborative inference.

Keywords

deep neural network acceleration deep neural network deep neural networks

Cite

@article{arxiv.2502.15312,
  title  = {FlexPie: Accelerate Distributed Inference on Edge Devices with Flexible Combinatorial Optimization[Technical Report]},
  author = {Runhua Zhang and Hongxu Jiang and Jinkun Geng and Yuhang Ma and Chenhui Zhu and Haojie Wang},
  journal= {arXiv preprint arXiv:2502.15312},
  year   = {2025}
}

Related papers

View all related →
Machine Learning · Computer Science
Scaling Up Deep Neural Network Optimization for Edge Inference
Bingqian Lu, Jianyi Yang, Shaolei Ren
2020-09-18
Distributed, Parallel, and Cluster Computing · Computer Science
DistrEE: Distributed Early Exit of Deep Neural Network Inference on Edge Devices
Xian Peng, Xin Wu, Lianming Xu, Li Wang +1
2025-02-25
Distributed, Parallel, and Cluster Computing · Computer Science
Edge Intelligence: On-Demand Deep Learning Model Co-Inference with Device-Edge Synergy
En Li, Zhi Zhou, Xu Chen
2018-12-31
Computer Vision and Pattern Recognition · Computer Science
Collaborative Execution of Deep Neural Networks on Internet of Things Devices
Ramyad Hadidi, Jiashen Cao, Micheal S. Ryoo, Hyesoon Kim
2019-01-10
Machine Learning · Computer Science
Enabling Deep Learning on Edge Devices
Zhongnan Qu
2022-10-10
Machine Learning · Computer Science
Decentralized Low-Latency Collaborative Inference via Ensembles on the Edge
May Malka, Erez Farhan, Hai Morgenstern, Nir Shlezinger
2022-06-08
Distributed, Parallel, and Cluster Computing · Computer Science
A Survey on Collaborative DNN Inference for Edge Intelligence
Weiqing Ren, Yuben Qu, Chao Dong, Yuqian Jing +3
2024-04-01
Distributed, Parallel, and Cluster Computing · Computer Science
Adaptive Device-Edge Collaboration on DNN Inference in AIoT: A Digital Twin-Assisted Approach
Shisheng Hu, Mushu Li, Jie Gao, Conghao Zhou +1
2024-05-29
Machine Learning · Computer Science
EmBench: Quantifying Performance Variations of Deep Neural Networks across Modern Commodity Devices
Mario Almeida, Stefanos Laskaridis, Ilias Leontiadis, Stylianos I. Venieris +1
2019-05-20
Machine Learning · Computer Science
FTPipeHD: A Fault-Tolerant Pipeline-Parallel Distributed Training Framework for Heterogeneous Edge Devices
Yuhao Chen, Qianqian Yang, Shibo He, Zhiguo Shi +1
2021-10-07
Computer Vision and Pattern Recognition · Computer Science
Deploying Deep Neural Networks in the Embedded Space
Stylianos I. Venieris, Alexandros Kouris, Christos-Savvas Bouganis
2018-06-25
Distributed, Parallel, and Cluster Computing · Computer Science
DistrEdge: Speeding up Convolutional Neural Network Inference on Distributed Edge Devices
Xueyu Hou, Yongjie Guan, Tao Han, Ning Zhang
2022-02-09
Machine Learning · Statistics
New Directions in Distributed Deep Learning: Bringing the Network at Forefront of IoT Design
Kartikeya Bhardwaj, Wei Chen, Radu Marculescu
2020-08-26
Machine Learning · Computer Science
InstantNet: Automated Generation and Deployment of Instantaneously Switchable-Precision Networks
Yonggan Fu, Zhongzhi Yu, Yongan Zhang, Yifan Jiang +5
2025-01-07
Distributed, Parallel, and Cluster Computing · Computer Science
SlimEdge: Performance and Device Aware Distributed DNN Deployment on Resource-Constrained Edge Hardware
Mahadev Sunil Kumar, Arnab Raha, Debayan Das, Gopakumar G +2
2026-02-17
Distributed, Parallel, and Cluster Computing · Computer Science
Embedded Distributed Inference of Deep Neural Networks: A Systematic Review
Federico Nicolás Peccia, Oliver Bringmann
2024-05-07
Computer Vision and Pattern Recognition · Computer Science
Distributed Deep Neural Networks over the Cloud, the Edge and End Devices
Surat Teerapittayanon, Bradley McDanel, H. T. Kung
2017-09-08
Machine Learning · Computer Science
On the Sustainability of AI Inferences in the Edge
Ghazal Sobhani, Md. Monzurul Amin Ifath, Tushar Sharma, Israat Haque
2025-08-01
Networking and Internet Architecture · Computer Science
Edge AI: On-Demand Accelerating Deep Neural Network Inference via Edge Computing
En Li, Liekang Zeng, Zhi Zhou, Xu Chen
2019-10-14
Machine Learning · Computer Science
Designing and Training of Lightweight Neural Networks on Edge Devices using Early Halting in Knowledge Distillation
Rahul Mishra, Hari Prabhat Gupta
2022-10-03
Machine Learning · Computer Science
Enable Deep Learning on Mobile Devices: Methods, Systems, and Applications
Han Cai, Ji Lin, Yujun Lin, Zhijian Liu +4
2022-04-26
Distributed, Parallel, and Cluster Computing · Computer Science
Auto-tuning Neural Network Quantization Framework for Collaborative Inference Between the Cloud and Edge
Guangli Li, Lei Liu, Xueying Wang, Xiao Dong +2
2018-12-19
Networking and Internet Architecture · Computer Science
Modeling of Deep Neural Network (DNN) Placement and Inference in Edge Computing
Mounir Bensalem, Jasenka Dizdarević, Admela Jukan
2020-03-12
Distributed, Parallel, and Cluster Computing · Computer Science
Edge-PRUNE: Flexible Distributed Deep Learning Inference
Jani Boutellier, Bo Tan, Jari Nurmi
2022-04-28
Machine Learning · Computer Science
Deep Learning at the Edge
Sahar Voghoei, Navid Hashemi Tonekaboni, Jason G. Wallace, Hamid R. Arabnia
2019-10-24
R2 v1 2026-06-28T21:52:32.211Z