Abstract: Graph neural networks (GNNs) are a widely-used class of deep learning (DL) models for learning latent representations of graph-structured data for a variety of node/graph-level prediction ...
Abstract: Most high-end computers adopt hybrid architecture, porting a large-scale scientific code onto accelerators is necessary. The paper presents a generic method for porting large-scale ...
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