Cover Image

Optimization of GNN Training Through Half-precision

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Tarafder, Arnab Kanti, Gong, Yidong, Kumar, Pradeep
Format:	Preprint
Published:	2024
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

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

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

Efficient GNN Training Through Structure-Aware Randomized Mini-Batching
by: Balaji, Vignesh, et al.
Published: (2025)

Enhancing PAC Learning of Half spaces Through Robust Optimization Techniques
by: Tavangari, Shirmohammad, et al.
Published: (2024)

Quantum Optimization for Training Quantum Neural Networks
by: Liao, Yidong, et al.
Published: (2021)

Adaptive Graph Coarsening for Efficient GNN Training
by: Olshevskyi, Rostyslav, et al.
Published: (2025)

DiskGNN: Bridging I/O Efficiency and Model Accuracy for Out-of-Core GNN Training
by: Liu, Renjie, et al.
Published: (2024)

Offline Safe Reinforcement Learning Using Trajectory Classification
by: Gong, Ze, et al.
Published: (2024)

GRID: Protecting Training Graph from Link Stealing Attacks on GNN Models
by: Lou, Jiadong, et al.
Published: (2025)

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

DFA-GNN: Forward Learning of Graph Neural Networks by Direct Feedback Alignment
by: Zhao, Gongpei, et al.
Published: (2024)

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

GNNMerge: Merging of GNN Models Without Accessing Training Data
by: Garg, Vipul, et al.
Published: (2025)

Provably Convergent Subgraph-wise Sampling for Fast GNN Training
by: Wang, Jie, et al.
Published: (2023)

Learning to Retrieve with Weakened Labels: Robust Training under Label Noise
by: Sharma, Arnab
Published: (2025)

Fast and Effective GNN Training through Sequences of Random Path Graphs
by: Bonchi, Francesco, et al.
Published: (2023)

ADMP-GNN: Adaptive Depth Message Passing GNN
by: Abbahaddou, Yassine, et al.
Published: (2025)

Optimal Asynchronous Stochastic Nonconvex Optimization under Heavy-Tailed Noise
by: Wu, Yidong, et al.
Published: (2026)

Bridging Training and Merging Through Momentum-Aware Optimization
by: Moayedikia, Alireza, et al.
Published: (2025)

HePGA: A Heterogeneous Processing-in-Memory based GNN Training Accelerator
by: Ogbogu, Chukwufumnanya, et al.
Published: (2025)

Using Retriever Augmented Large Language Models for Attack Graph Generation
by: Prapty, Renascence Tarafder, et al.
Published: (2024)

DR-CircuitGNN: Training Acceleration of Heterogeneous Circuit Graph Neural Network on GPUs
by: Luo, Yuebo, et al.
Published: (2025)

SmoothGNN: Smoothing-aware GNN for Unsupervised Node Anomaly Detection
by: Dong, Xiangyu, et al.
Published: (2024)

$P^2$GNN: Two Prototype Sets to boost GNN Performance
by: Jain, Arihant, et al.
Published: (2026)

FlashAttention-3: Fast and Accurate Attention with Asynchrony and Low-precision
by: Shah, Jay, et al.
Published: (2024)

FARe: Fault-Aware GNN Training on ReRAM-based PIM Accelerators
by: Dhingra, Pratyush, et al.
Published: (2024)

Sketch-GNN: Scalable Graph Neural Networks with Sublinear Training Complexity
by: Ding, Mucong, et al.
Published: (2024)

Training a Label-Noise-Resistant GNN with Reduced Complexity
by: Zhao, Rui, et al.
Published: (2024)

InversionGNN: A Dual Path Network for Multi-Property Molecular Optimization
by: Niu, Yifan, et al.
Published: (2025)

Neural Network Training with Approximate Logarithmic Computations
by: Sanyal, Arnab, et al.
Published: (2019)

MQ-GNN: A Multi-Queue Pipelined Architecture for Scalable and Efficient GNN Training
by: Ullah, Irfan, et al.
Published: (2026)

Towards Optimization and Model Selection for Domain Generalization: A Mixup-guided Solution
by: Lu, Wang, et al.
Published: (2022)

Is the GPU Half-Empty or Half-Full? Practical Scheduling Techniques for LLMs
by: Kossmann, Ferdi, et al.
Published: (2024)

Disttack: Graph Adversarial Attacks Toward Distributed GNN Training
by: Zhang, Yuxiang, et al.
Published: (2024)

FreshGNN: Reducing Memory Access via Stable Historical Embeddings for Graph Neural Network Training
by: Huang, Kezhao, et al.
Published: (2023)

Improved Canonicalization for Model Agnostic Equivariance
by: Panigrahi, Siba Smarak, et al.
Published: (2024)

On GNN explanability with activation rules
by: Veyrin-Forrer, Luca, et al.
Published: (2024)

On The Expressive Power of GNN Derivatives
by: Eitan, Yam, et al.
Published: (2025)

MDAS-GNN: Multi-Dimensional Spatiotemporal GNN with Spatial Diffusion for Urban Traffic Risk Forecasting
by: Gao, Ziyuan
Published: (2025)

MuseGNN: Forming Scalable, Convergent GNN Layers that Minimize a Sampling-Based Energy
by: Jiang, Haitian, et al.
Published: (2023)