89 citations · 194 across the 58 of their papers we have counts for
Showing 2021Show all
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cs.LG2021★ 21 cited
Understanding GNN Computational Graph: A Coordinated Computation, IO, and Memory Perspective
Hengrui Zhang, Zhongming Yu, Guohao Dai +4
Graph Neural Networks (GNNs) have been widely used in various domains, and GNNs with sophisticated computational graph lead to higher latency and larger memory consumption. Optimiz…
cs.DC2021★ 1 cited
Efficient Sparse Matrix Kernels based on Adaptive Workload-Balancing and Parallel-Reduction
Guyue Huang, Guohao Dai, Yu Wang +2
Sparse matrix-vector and matrix-matrix multiplication (SpMV and SpMM) are fundamental in both conventional (graph analytics, scientific computing) and emerging (sparse DNN, GNN) do…
cs.SI2021★ 5 cited
CogDL: A Comprehensive Library for Graph Deep Learning
Yukuo Cen, Zhenyu Hou, Yan Wang +15
Graph neural networks (GNNs) have attracted tremendous attention from the graph learning community in recent years. It has been widely adopted in various real-world applications fr…