Comprehensive Evaluation of GNN Training Systems: A Data Management Perspective
Fuente:
arXiv
Saved in:
| Main Authors: | Yuan, Hao, Liu, Yajiong, Zhang, Yanfeng, Ai, Xin, Wang, Qiange, Chen, Chaoyi, Gu, Yu, Yu, Ge |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
NeutronTP: Load-Balanced Distributed Full-Graph GNN Training with Tensor Parallelism
by: Ai, Xin, et al.
Published: (2024)
by: Ai, Xin, et al.
Published: (2024)
AcOrch: Accelerating Sampling-based GNN Training under CPU-NPU Heterogeneous Environments
by: Chen, Kefu, et al.
Published: (2026)
by: Chen, Kefu, et al.
Published: (2026)
Incremental GNN Embedding Computation on Streaming Graphs
by: Wang, Qiange, et al.
Published: (2026)
by: Wang, Qiange, et al.
Published: (2026)
HopGNN: Boosting Distributed GNN Training Efficiency via Feature-Centric Model Migration
by: Chen, Weijian, et al.
Published: (2024)
by: Chen, Weijian, et al.
Published: (2024)
ARGO: An Auto-Tuning Runtime System for Scalable GNN Training on Multi-Core Processor
by: Lin, Yi-Chien, et al.
Published: (2024)
by: Lin, Yi-Chien, et al.
Published: (2024)
MegatronApp: Efficient and Comprehensive Management on Distributed LLM Training
by: Zhao, Bohan, et al.
Published: (2025)
by: Zhao, Bohan, et al.
Published: (2025)
GreenDyGNN: Runtime-Adaptive Energy-Efficient Communication for Distributed GNN Training
by: Niam, Arefin, et al.
Published: (2026)
by: Niam, Arefin, et al.
Published: (2026)
A Unified CPU-GPU Protocol for GNN Training
by: Lin, Yi-Chien, et al.
Published: (2024)
by: Lin, Yi-Chien, et al.
Published: (2024)
Scaling Large-scale GNN Training to Thousands of Processors on CPU-based Supercomputers
by: Zhuang, Chen, et al.
Published: (2024)
by: Zhuang, Chen, et al.
Published: (2024)
Fast Iterative Graph Computing with Updated Neighbor States
by: Zhou, Yijie, et al.
Published: (2024)
by: Zhou, Yijie, et al.
Published: (2024)
ACE-GNN: Adaptive GNN Co-Inference with System-Aware Scheduling in Dynamic Edge Environments
by: Zhou, Ao, et al.
Published: (2025)
by: Zhou, Ao, et al.
Published: (2025)
Hierarchical Prediction-based Management for LMaaS Systems
by: Jiang, Zhihan, et al.
Published: (2025)
by: Jiang, Zhihan, et al.
Published: (2025)
Towards Affordable, Adaptive and Automatic GNN Training on CPU-GPU Heterogeneous Platforms
by: Qiao, Tong, et al.
Published: (2025)
by: Qiao, Tong, et al.
Published: (2025)
Understanding and Reducing Metadata-Driven Host Overheads in Sampling-Based GNN Training
by: Gong, Yidong, et al.
Published: (2026)
by: Gong, Yidong, et al.
Published: (2026)
DistTrain: Addressing Model and Data Heterogeneity with Disaggregated Training for Multimodal Large Language Models
by: Zhang, Zili, et al.
Published: (2024)
by: Zhang, Zili, et al.
Published: (2024)
RapidGNN: Communication Efficient Large-Scale Distributed Training of Graph Neural Networks
by: Niam, Arefin, et al.
Published: (2025)
by: Niam, Arefin, et al.
Published: (2025)
CondenseGraph: Communication-Efficient Distributed GNN Training via On-the-Fly Graph Condensation
by: Zhang, Zizhao, et al.
Published: (2026)
by: Zhang, Zizhao, 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)
by: Park, Jeongmin Brian, et al.
Published: (2024)
GriNNder: Breaking the Memory Capacity Wall in Full-Graph GNN Training with Storage Offloading
by: Song, Jaeyong, et al.
Published: (2026)
by: Song, Jaeyong, 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)
by: Maharaj, Davendra, et al.
Published: (2026)
FaaSTube: Optimizing GPU-oriented Data Transfer for Serverless Computing
by: Wu, Hao, et al.
Published: (2024)
by: Wu, Hao, et al.
Published: (2024)
Lagom: Unleashing the Power of Communication and Computation Overlapping for Distributed LLM Training
by: Xu, Guanbin, et al.
Published: (2026)
by: Xu, Guanbin, et al.
Published: (2026)
Hiding Communication Cost in Distributed LLM Training via Micro-batch Co-execution
by: Wang, Haiquan, et al.
Published: (2024)
by: Wang, Haiquan, et al.
Published: (2024)
LoongTrain: Efficient Training of Long-Sequence LLMs with Head-Context Parallelism
by: Gu, Diandian, et al.
Published: (2024)
by: Gu, Diandian, et al.
Published: (2024)
SDT-GNN: Streaming-based Distributed Training Framework for Graph Neural Networks
by: Huang, Xin, et al.
Published: (2024)
by: Huang, Xin, et al.
Published: (2024)
On Fault Tolerance of Data Storage Systems: A Holistic Perspective
by: Zheng, Mai, et al.
Published: (2025)
by: Zheng, Mai, et al.
Published: (2025)
Data Management System Analysis for Distributed Computing Workloads
by: Hsu, Kuan-Chieh, et al.
Published: (2025)
by: Hsu, Kuan-Chieh, et al.
Published: (2025)
ElasWave: An Elastic-Native System for Scalable Hybrid-Parallel Training
by: Kang, Xueze, et al.
Published: (2025)
by: Kang, Xueze, et al.
Published: (2025)
Malleus: Straggler-Resilient Hybrid Parallel Training of Large-scale Models via Malleable Data and Model Parallelization
by: Li, Haoyang, et al.
Published: (2024)
by: Li, Haoyang, et al.
Published: (2024)
D-CAST: Distributed Consensus Switch in Wireless Trustworthy Autonomous System
by: Yu, Dachao, et al.
Published: (2024)
by: Yu, Dachao, et al.
Published: (2024)
Cortex: Achieving Low-Latency, Cost-Efficient Remote Data Access For LLM via Semantic-Aware Knowledge Caching
by: Ruan, Chaoyi, et al.
Published: (2025)
by: Ruan, Chaoyi, et al.
Published: (2025)
Accelerating Heterogeneous Tensor Parallelism via Flexible Workload Control
by: Wang, Zhigang, et al.
Published: (2024)
by: Wang, Zhigang, et al.
Published: (2024)
RIPPLE++: An Incremental Framework for Efficient GNN Inference on Evolving Graphs
by: Naman, Pranjal, et al.
Published: (2026)
by: Naman, Pranjal, et al.
Published: (2026)
Ripple: Scalable Incremental GNN Inferencing on Large Streaming Graphs
by: Naman, Pranjal, et al.
Published: (2025)
by: Naman, Pranjal, et al.
Published: (2025)
Oases: Efficient Large-Scale Model Training on Commodity Servers via Overlapped and Automated Tensor Model Parallelism
by: Li, Shengwei, et al.
Published: (2023)
by: Li, Shengwei, et al.
Published: (2023)
Reaching Agreement Among Reasoning LLM Agents
by: Ruan, Chaoyi, et al.
Published: (2025)
by: Ruan, Chaoyi, et al.
Published: (2025)
MTGenRec: An Efficient Distributed Training System for Generative Recommendation Models in Meituan
by: Wang, Yuxiang, et al.
Published: (2025)
by: Wang, Yuxiang, et al.
Published: (2025)
Hetu v2: A General and Scalable Deep Learning System with Hierarchical and Heterogeneous Single Program Multiple Data Annotations
by: Li, Haoyang, et al.
Published: (2025)
by: Li, Haoyang, et al.
Published: (2025)
Next-Gen Computing Systems with Compute Express Link: a Comprehensive Survey
by: Chen, Chen, et al.
Published: (2024)
by: Chen, Chen, et al.
Published: (2024)
Lattica: A Decentralized Cross-NAT Communication Framework for Scalable AI Inference and Training
by: Yang, Ween, et al.
Published: (2025)
by: Yang, Ween, et al.
Published: (2025)
Similar Items
-
NeutronTP: Load-Balanced Distributed Full-Graph GNN Training with Tensor Parallelism
by: Ai, Xin, et al.
Published: (2024) -
AcOrch: Accelerating Sampling-based GNN Training under CPU-NPU Heterogeneous Environments
by: Chen, Kefu, et al.
Published: (2026) -
Incremental GNN Embedding Computation on Streaming Graphs
by: Wang, Qiange, et al.
Published: (2026) -
HopGNN: Boosting Distributed GNN Training Efficiency via Feature-Centric Model Migration
by: Chen, Weijian, et al.
Published: (2024) -
ARGO: An Auto-Tuning Runtime System for Scalable GNN Training on Multi-Core Processor
by: Lin, Yi-Chien, et al.
Published: (2024)