davide-gurrieri/parallel-GCN
High-performance CUDA C++ implementation of Graph Convolutional Networks
This project offers a high-performance implementation of Graph Convolutional Networks (GCNs) for data classification tasks. It takes graph-structured datasets as input and outputs classifications with improved speed and accuracy. This is designed for data scientists or machine learning engineers who need to quickly process large graph datasets for tasks like document classification or social network analysis.
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Use this if you are a machine learning engineer working with graph-structured data and need to perform classifications much faster than traditional methods, while maintaining high accuracy.
Not ideal if you are not comfortable working in a CUDA C++ environment or if your primary goal is not high-performance graph classification.
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C++
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Last pushed
Jun 11, 2023
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