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Found 3 papers, 1 papers with code
Motif Prediction with Graph Neural Networks
We also successfully apply our architecture for predicting more arbitrary clusters and communities, illustrating its potential for graph mining beyond motif analysis.
GraphMineSuite: Enabling High-Performance and Programmable Graph Mining Algorithms with Set Algebra
We propose GraphMineSuite (GMS): the first benchmarking suite for graph mining that facilitates evaluating and constructing high-performance graph mining algorithms.
Red-blue pebbling revisited: near optimal parallel matrix-matrix multiplication
The key idea behind COSMA is to derive an optimal (up to a factor of 0. 03\% for 10MB of fast memory) sequential schedule and then parallelize it, preserving I/O optimality.
Computational Complexity Distributed, Parallel, and Cluster Computing Performance
