Graph Neural Networks as Ordering Heuristics for Parallel Graph Coloring
Fuente:
arXiv
Saved in:
| Main Authors: | Langedal, Kenneth, Manne, Fredrik |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
GSplit: Scaling Graph Neural Network Training on Large Graphs via Split-Parallelism
by: Polisetty, Sandeep, et al.
Published: (2023)
by: Polisetty, Sandeep, et al.
Published: (2023)
Graph Neural Networks Gone Hogwild
by: Solodova, Olga, et al.
Published: (2024)
by: Solodova, Olga, et al.
Published: (2024)
Cooperative Minibatching in Graph Neural Networks
by: Balin, Muhammed Fatih, et al.
Published: (2023)
by: Balin, Muhammed Fatih, et al.
Published: (2023)
Edge-Parallel Graph Encoder Embedding
by: Lubonja, Ariel, et al.
Published: (2024)
by: Lubonja, Ariel, et al.
Published: (2024)
Graph Neural Network Training Systems: A Performance Comparison of Full-Graph and Mini-Batch
by: Bajaj, Saurabh, et al.
Published: (2024)
by: Bajaj, Saurabh, et al.
Published: (2024)
Fully Distributed Online Training of Graph Neural Networks in Networked Systems
by: Olshevskyi, Rostyslav, et al.
Published: (2024)
by: Olshevskyi, Rostyslav, et al.
Published: (2024)
ReInc: Scaling Training of Dynamic Graph Neural Networks
by: Guan, Mingyu, et al.
Published: (2025)
by: Guan, Mingyu, et al.
Published: (2025)
Federated Incomplete Multi-View Clustering with Heterogeneous Graph Neural Networks
by: Yan, Xueming, et al.
Published: (2024)
by: Yan, Xueming, et al.
Published: (2024)
Graph Neural Networks and Reinforcement Learning for Proactive Application Image Placement
by: Makris, Antonios, et al.
Published: (2024)
by: Makris, Antonios, et al.
Published: (2024)
Optimizing Federated Learning using Remote Embeddings for Graph Neural Networks
by: Naman, Pranjal, et al.
Published: (2025)
by: Naman, Pranjal, et al.
Published: (2025)
Grappa: Gradient-Only Communication for Scalable Graph Neural Network Training
by: Xu, Chongyang, et al.
Published: (2026)
by: Xu, Chongyang, et al.
Published: (2026)
An Experimental Comparison of Partitioning Strategies for Distributed Graph Neural Network Training
by: Merkel, Nikolai, et al.
Published: (2023)
by: Merkel, Nikolai, et al.
Published: (2023)
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)
Armada: Memory-Efficient Distributed Training of Large-Scale Graph Neural Networks
by: Waleffe, Roger, et al.
Published: (2025)
by: Waleffe, Roger, et al.
Published: (2025)
High Order Collaboration-Oriented Federated Graph Neural Network for Accurate QoS Prediction
by: Chen, Zehuan, et al.
Published: (2025)
by: Chen, Zehuan, et al.
Published: (2025)
ViBE: Co-Optimizing Workload Skew and Hardware Variability for MoE Serving
by: Go, Seokjin, et al.
Published: (2026)
by: Go, Seokjin, et al.
Published: (2026)
EmbedPart: Embedding-Driven Graph Partitioning for Scalable Graph Neural Network Training
by: Merkel, Nikolai, et al.
Published: (2026)
by: Merkel, Nikolai, et al.
Published: (2026)
GeoT: Tensor Centric Library for Graph Neural Network via Efficient Segment Reduction on GPU
by: Yu, Zhongming, et al.
Published: (2024)
by: Yu, Zhongming, et al.
Published: (2024)
Distributed Matrix-Based Sampling for Graph Neural Network Training
by: Tripathy, Alok, et al.
Published: (2023)
by: Tripathy, Alok, et al.
Published: (2023)
Scalable and Adaptive Parallel Training of Graph Transformer on Large Graphs
by: Lin, Jun-Liang, et al.
Published: (2026)
by: Lin, Jun-Liang, et al.
Published: (2026)
Enhancing Physics-Informed Neural Networks with a Hybrid Parallel Kolmogorov-Arnold and MLP Architecture
by: Xu, Zuyu, et al.
Published: (2025)
by: Xu, Zuyu, et al.
Published: (2025)
CDFGNN: a Systematic Design of Cache-based Distributed Full-Batch Graph Neural Network Training with Communication Reduction
by: Zhang, Shuai, et al.
Published: (2024)
by: Zhang, Shuai, et al.
Published: (2024)
Leveraging Neural Graph Compilers in Machine Learning Research for Edge-Cloud Systems
by: Furutanpey, Alireza, et al.
Published: (2025)
by: Furutanpey, Alireza, et al.
Published: (2025)
GraphPipe: Improving Performance and Scalability of DNN Training with Graph Pipeline Parallelism
by: Jeon, Byungsoo, et al.
Published: (2024)
by: Jeon, Byungsoo, et al.
Published: (2024)
Distributed Graph Neural Network Inference With Just-In-Time Compilation For Industry-Scale Graphs
by: Wu, Xiabao, et al.
Published: (2025)
by: Wu, Xiabao, et al.
Published: (2025)
Ordered Momentum for Asynchronous SGD
by: Shi, Chang-Wei, et al.
Published: (2024)
by: Shi, Chang-Wei, et al.
Published: (2024)
FedGAT: A Privacy-Preserving Federated Approximation Algorithm for Graph Attention Networks
by: Ambekar, Siddharth, et al.
Published: (2024)
by: Ambekar, Siddharth, et al.
Published: (2024)
Rel-HNN: Split Parallel Hypergraph Neural Network for Learning on Relational Databases
by: Alam, Md. Tanvir, et al.
Published: (2025)
by: Alam, Md. Tanvir, et al.
Published: (2025)
CaPGNN: Optimizing Parallel Graph Neural Network Training with Joint Caching and Resource-Aware Graph Partitioning
by: Song, Xianfeng, et al.
Published: (2025)
by: Song, Xianfeng, et al.
Published: (2025)
Federated Temporal Graph Clustering
by: Zhou, Zihao, et al.
Published: (2024)
by: Zhou, Zihao, et al.
Published: (2024)
Scalable and Consistent Graph Neural Networks for Distributed Mesh-based Data-driven Modeling
by: Barwey, Shivam, et al.
Published: (2024)
by: Barwey, Shivam, et al.
Published: (2024)
iSpLib: A Library for Accelerating Graph Neural Networks using Auto-tuned Sparse Operations
by: Anik, Md Saidul Hoque, et al.
Published: (2024)
by: Anik, Md Saidul Hoque, et al.
Published: (2024)
Federated Graph Learning with Graphless Clients
by: Fu, Xingbo, et al.
Published: (2024)
by: Fu, Xingbo, et al.
Published: (2024)
Ariel-ML: Computing Parallelization with Embedded Rust for Neural Networks on Heterogeneous Multi-core Microcontrollers
by: Huang, Zhaolan, et al.
Published: (2025)
by: Huang, Zhaolan, et al.
Published: (2025)
Graph-Regularized Learning of Gaussian Mixture Models
by: Abdurakhmanova, Shamsiiat, et al.
Published: (2025)
by: Abdurakhmanova, Shamsiiat, et al.
Published: (2025)
NOMAD: Generating Embeddings for Massive Distributed Graphs
by: Sarkar, Aishwarya, et al.
Published: (2026)
by: Sarkar, Aishwarya, et al.
Published: (2026)
Distributed Graph Embedding with Information-Oriented Random Walks
by: Fang, Peng, et al.
Published: (2023)
by: Fang, Peng, et al.
Published: (2023)
Knowledge-Driven Federated Graph Learning on Model Heterogeneity
by: Wu, Zhengyu, et al.
Published: (2025)
by: Wu, Zhengyu, et al.
Published: (2025)
Semi-decentralized Training of Spatio-Temporal Graph Neural Networks for Traffic Prediction
by: Kralj, Ivan, et al.
Published: (2024)
by: Kralj, Ivan, et al.
Published: (2024)
D3-GNN: Dynamic Distributed Dataflow for Streaming Graph Neural Networks
by: Guliyev, Rustam, et al.
Published: (2024)
by: Guliyev, Rustam, et al.
Published: (2024)
Similar Items
-
GSplit: Scaling Graph Neural Network Training on Large Graphs via Split-Parallelism
by: Polisetty, Sandeep, et al.
Published: (2023) -
Graph Neural Networks Gone Hogwild
by: Solodova, Olga, et al.
Published: (2024) -
Cooperative Minibatching in Graph Neural Networks
by: Balin, Muhammed Fatih, et al.
Published: (2023) -
Edge-Parallel Graph Encoder Embedding
by: Lubonja, Ariel, et al.
Published: (2024) -
Graph Neural Network Training Systems: A Performance Comparison of Full-Graph and Mini-Batch
by: Bajaj, Saurabh, et al.
Published: (2024)