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Found 3 papers, 2 papers with code
NeutronOrch: Rethinking Sample-based GNN Training under CPU-GPU Heterogeneous Environments
After extensive experiments and analysis, we find that existing task orchestrating methods fail to fully utilize the heterogeneous resources, limited by inefficient CPU processing or GPU resource contention.
Comprehensive Evaluation of GNN Training Systems: A Data Management Perspective
Many Graph Neural Network (GNN) training systems have emerged recently to support efficient GNN training.
DeepOHeat: Operator Learning-based Ultra-fast Thermal Simulation in 3D-IC Design
In this paper, for the first time, we propose DeepOHeat, a physics-aware operator learning framework to predict the temperature field of a family of heat equations with multiple parametric or non-parametric design configurations.
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