most citedPyGim: An Efficient Graph Neural Network Library for Real Processing-In-Memory Architectures

3 citations · 3 across the 1 of their papers we have counts for

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cs.AR2024★ 3 cited

PyGim: An Efficient Graph Neural Network Library for Real Processing-In-Memory Architectures

Christina Giannoula, Peiming Yang, Ivan Fernandez +7

Graph Neural Networks (GNNs) are emerging ML models to analyze graph-structure data. Graph Neural Network (GNN) execution involves both compute-intensive and memory-intensive kerne…