Jun 3, 2024 · To render this coordinated optimization impactful, a rule-based computational graph optimization and a performance-driven operator optimization ...
Jun 4, 2024 · Computational graph optimization for GNNs involves rewriting the computational graph by identifying specific pattern operators and replacing ...
Jun 6, 2024 · A Coordinated Strategy for GNN Combining Computational Graph and Operator Optimizations ; Mingyi Li ; Junmin Xiao ; Kewei Zhang ; Zhiheng Lin.
Oct 18, 2021 · GNN computation graph optimization includes operator reorganization, operator fusion, data flow optimization, etc., and many efforts have ...
PyG supports important GNN building blocks that can be combined and applied to various parts of a GNN model, ensuring rich flexibility of GNN design. Finally, ...
We propose following designs to optimize the GNN computational graph from a novel coordinated computation, IO, and memory perspective.
Missing: Strategy Combining
The following designs to optimize the GNN computational graph from a novel coordinated computation, IO, and memory perspective are proposed: ...
A Coordinated Strategy for GNN Combining Computational Graph and Operator Optimizations · Exploiting Fine-Grained Redundancy in Set-Centric Graph Pattern Mining.
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Aug 28, 2024 · A Coordinated Strategy for GNN Combining Computational Graph and Operator Optimizations. Mingyi Li, Junmin Xiao, Kewei Zhang, Zhiheng Lin ...
sampling methods and the operator layer abstracts the GNN computation with two kinds of operators. Users can define their own models by choosing their ...