PipeSD: An Efficient Cloud-Edge Collaborative Pipeline Inference Framework with Speculative Decoding
Fuente:
arXiv
Saved in:
| Main Authors: | Han, Yunhe, Gao, Yunqi, Hu, Bing, Mashhadi, Mahdi Boloursaz, Duan, Yitong, Xiao, Pei, Zhang, Yanfeng |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
FlowMoE: A Scalable Pipeline Scheduling Framework for Distributed Mixture-of-Experts Training
by: Gao, Yunqi, et al.
Published: (2025)
by: Gao, Yunqi, et al.
Published: (2025)
A Pipelined Collaborative Speculative Decoding Framework for Efficient Edge-Cloud LLM Inference
by: Zhang, Yida, et al.
Published: (2026)
by: Zhang, Yida, et al.
Published: (2026)
FlexSpec: Frozen Drafts Meet Evolving Targets in Edge-Cloud Collaborative LLM Speculative Decoding
by: Li, Yuchen, et al.
Published: (2026)
by: Li, Yuchen, et al.
Published: (2026)
ECCENTRIC: Edge-Cloud Collaboration Framework for Distributed Inference Using Knowledge Adaptation
by: Kamani, Mohammad Mahdi, et al.
Published: (2025)
by: Kamani, Mohammad Mahdi, et al.
Published: (2025)
FlowSpec: Continuous Pipelined Speculative Decoding for Efficient Distributed LLM Inference
by: Liu, Xing, et al.
Published: (2025)
by: Liu, Xing, et al.
Published: (2025)
Ghidorah: Fast LLM Inference on Edge with Speculative Decoding and Hetero-Core Parallelism
by: Wei, Jinhui, et al.
Published: (2025)
by: Wei, Jinhui, et al.
Published: (2025)
GoodSpeed: Optimizing Fair Goodput with Adaptive Speculative Decoding in Distributed Edge Inference
by: Tran, Phuong, et al.
Published: (2025)
by: Tran, Phuong, et al.
Published: (2025)
SiPipe: Bridging the CPU-GPU Utilization Gap for Efficient Pipeline-Parallel LLM Inference
by: He, Yongchao, et al.
Published: (2025)
by: He, Yongchao, et al.
Published: (2025)
PipeInfer: Accelerating LLM Inference using Asynchronous Pipelined Speculation
by: Butler, Branden, et al.
Published: (2024)
by: Butler, Branden, et al.
Published: (2024)
DiffusionPipe: Training Large Diffusion Models with Efficient Pipelines
by: Tian, Ye, et al.
Published: (2024)
by: Tian, Ye, et al.
Published: (2024)
MSAO: Adaptive Modality Sparsity-Aware Offloading with Edge-Cloud Collaboration for Efficient Multimodal LLM Inference
by: Yang, Zheming, et al.
Published: (2026)
by: Yang, Zheming, et al.
Published: (2026)
Collaborative Speculative Inference for Efficient LLM Inference Serving
by: Gao, Luyao, et al.
Published: (2025)
by: Gao, Luyao, et al.
Published: (2025)
Accelerating End-Cloud Collaborative Inference via Near Bubble-free Pipeline Optimization
by: Gao, Luyao, et al.
Published: (2024)
by: Gao, Luyao, et al.
Published: (2024)
EdgeShard: Efficient LLM Inference via Collaborative Edge Computing
by: Zhang, Mingjin, et al.
Published: (2024)
by: Zhang, Mingjin, et al.
Published: (2024)
TD-Pipe: Temporally-Disaggregated Pipeline Parallelism Architecture for High-Throughput LLM Inference
by: Zhang, Hongbin, et al.
Published: (2025)
by: Zhang, Hongbin, et al.
Published: (2025)
Accelerating OpenPangu Inference on NPU via Speculative Decoding
by: Dai, Yuntao, et al.
Published: (2026)
by: Dai, Yuntao, et al.
Published: (2026)
JanusPipe: Efficient Pipeline Parallel Training for Machine Learning Interatomic Potentials
by: Wang, Hongyu, et al.
Published: (2026)
by: Wang, Hongyu, et al.
Published: (2026)
PipeLLM: Fast and Confidential Large Language Model Services with Speculative Pipelined Encryption
by: Tan, Yifan, et al.
Published: (2024)
by: Tan, Yifan, et al.
Published: (2024)
MoA-Off: Adaptive Heterogeneous Modality-Aware Offloading with Edge-Cloud Collaboration for Efficient Multimodal LLM Inference
by: Yang, Zheming, et al.
Published: (2025)
by: Yang, Zheming, et al.
Published: (2025)
Accelerating Mixture-of-Experts Inference by Hiding Offloading Latency with Speculative Decoding
by: Wang, Zhibin, et al.
Published: (2025)
by: Wang, Zhibin, et al.
Published: (2025)
Fast and Cost-effective Speculative Edge-Cloud Decoding with Early Exits
by: Venkatesha, Yeshwanth, et al.
Published: (2025)
by: Venkatesha, Yeshwanth, et al.
Published: (2025)
Environment-Aware Dynamic Pruning for Pipelined Edge Inference
by: O'Quinn, Austin, et al.
Published: (2025)
by: O'Quinn, Austin, et al.
Published: (2025)
EC2MoE: Adaptive End-Cloud Pipeline Collaboration Enabling Scalable Mixture-of-Experts Inference
by: Yang, Zheming, et al.
Published: (2025)
by: Yang, Zheming, et al.
Published: (2025)
ML-ECS: A Collaborative Multimodal Learning Framework for Edge-Cloud Synergies
by: Liu, Yuze, et al.
Published: (2026)
by: Liu, Yuze, et al.
Published: (2026)
DSD: A Distributed Speculative Decoding Solution for Edge-Cloud Agile Large Model Serving
by: Yu, Fengze, et al.
Published: (2025)
by: Yu, Fengze, et al.
Published: (2025)
Efficient Routing of Inference Requests across LLM Instances in Cloud-Edge Computing
by: Yu, Shibo, et al.
Published: (2025)
by: Yu, Shibo, et al.
Published: (2025)
KCES: A Workflow Containerization Scheduling Scheme Under Cloud-Edge Collaboration Framework
by: Shan, Chenggang, et al.
Published: (2024)
by: Shan, Chenggang, et al.
Published: (2024)
HybridFlow: Resource-Adaptive Subtask Routing for Efficient Edge-Cloud LLM Inference
by: Dong, Jiangwen, et al.
Published: (2025)
by: Dong, Jiangwen, et al.
Published: (2025)
Collaborative Inference and Learning between Edge SLMs and Cloud LLMs: A Survey of Algorithms, Execution, and Open Challenges
by: Li, Senyao, et al.
Published: (2025)
by: Li, Senyao, et al.
Published: (2025)
SP-MoE: Speculative Decoding and Prefetching for Accelerating MoE-based Model Inference
by: Chen, Liangkun, et al.
Published: (2025)
by: Chen, Liangkun, et al.
Published: (2025)
Adaptive Configuration Selection for Multi-Model Inference Pipelines in Edge Computing
by: Sheng, Jinhao, et al.
Published: (2025)
by: Sheng, Jinhao, et al.
Published: (2025)
PipeBoost: Resilient Pipelined Architecture for Fast Serverless LLM Scaling
by: Liu, Chongpeng, et al.
Published: (2025)
by: Liu, Chongpeng, et al.
Published: (2025)
CrossPipe: Towards Optimal Pipeline Schedules for Cross-Datacenter Training
by: Chen, Tiancheng, et al.
Published: (2025)
by: Chen, Tiancheng, et al.
Published: (2025)
A Non-Intrusive Framework for Deferred Integration of Cloud Patterns in Energy-Efficient Data-Sharing Pipelines
by: Masoudi, Sepideh, et al.
Published: (2025)
by: Masoudi, Sepideh, et al.
Published: (2025)
Distributed Speculative Execution for Resilient Cloud Applications
by: Li, Tianyu, et al.
Published: (2024)
by: Li, Tianyu, et al.
Published: (2024)
Propius: A Platform for Collaborative Machine Learning across the Edge and the Cloud
by: Ding, Eric
Published: (2025)
by: Ding, Eric
Published: (2025)
Artifact for A Non-Intrusive Framework for Deferred Integration of Cloud Patterns in Energy-Efficient Data-Sharing Pipelines
by: Masoudi, Sepideh, et al.
Published: (2025)
by: Masoudi, Sepideh, et al.
Published: (2025)
ECC-SNN: Cost-Effective Edge-Cloud Collaboration for Spiking Neural Networks
by: Yu, Di, et al.
Published: (2025)
by: Yu, Di, et al.
Published: (2025)
Online Optimization of DNN Inference Network Utility in Collaborative Edge Computing
by: Li, Rui, et al.
Published: (2024)
by: Li, Rui, et al.
Published: (2024)
SkipPipe: Partial and Reordered Pipelining Framework for Training LLMs in Heterogeneous Networks
by: Blagoev, Nikolay, et al.
Published: (2025)
by: Blagoev, Nikolay, et al.
Published: (2025)
Similar Items
-
FlowMoE: A Scalable Pipeline Scheduling Framework for Distributed Mixture-of-Experts Training
by: Gao, Yunqi, et al.
Published: (2025) -
A Pipelined Collaborative Speculative Decoding Framework for Efficient Edge-Cloud LLM Inference
by: Zhang, Yida, et al.
Published: (2026) -
FlexSpec: Frozen Drafts Meet Evolving Targets in Edge-Cloud Collaborative LLM Speculative Decoding
by: Li, Yuchen, et al.
Published: (2026) -
ECCENTRIC: Edge-Cloud Collaboration Framework for Distributed Inference Using Knowledge Adaptation
by: Kamani, Mohammad Mahdi, et al.
Published: (2025) -
FlowSpec: Continuous Pipelined Speculative Decoding for Efficient Distributed LLM Inference
by: Liu, Xing, et al.
Published: (2025)