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Fix README to add cugraph modules. (#143)
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- Add cugraph module to README
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@jmatak
jmatak authored May 23, 2022
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Expand Up @@ -215,14 +215,15 @@ YIELD node, rank;
## MAGE Spells

| Algorithms | Lang | Description |
|----------------------------------------------------------------------------------------------------| ------ |-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| -------------------------------------------------------------------------------------------------- | ------ | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| [betweenness_centrality](cpp/betweenness_centrality_module/betweenness_centrality_module.cpp) | C++ | The betweenness centrality of a node is defined as the sum of the of all-pairs shortest paths that pass through the node divided by the number of all-pairs shortest paths in the graph. The algorithm has O(nm) time complexity. |
| [biconnected_components](cpp/biconnected_components_module/biconnected_components_module.cpp) | C++ | An algorithm for calculating maximal biconnected subgraph. A biconnected subgraph is a subgraph with a property that if any vertex were to be removed, the graph will remain connected. |
| [bipartite_matching](cpp/bipartite_matching_module/bipartite_matching_module.cpp) | C++ | An algorithm for calculating maximum bipartite matching, where matching is a set of nodes chosen in such a way that no two edges share an endpoint. |
| [bridges](cpp/bridges_module/bridges_module.cpp) | C++ | A bridge is an edge, which when deleted, increases the number of connected components. The goal of this algorithm is to detect edges that are bridges in a graph. |
| [community_detection](/mage/query-modules/cpp/community-detection) | C++ | The Louvain method for community detection is a greedy method for finding communities with maximum modularity in a graph. Runs in *O*(*n*log*n*) time. |
| [community_detection](/mage/query-modules/cpp/community-detection) | C++ | The Louvain method for community detection is a greedy method for finding communities with maximum modularity in a graph. Runs in _O_(*n*log*n*) time. |
| [community_detection_online](cpp/community_detection_module/community_detection_online_module.cpp) | C++ | A dynamic community detection algorithm suitable for large-scale graphs based upon label propagation. Runs in O(m) time and has O(mn) space complexity. |
| [cycles](cpp/cycles_module/cycles_module.cpp) | C++ | Algorithm for detecting cycles on graphs |
| [cugraph](/mage/query-modules/cuda/cugraph) | CUDA | Collection of NVIDIA GPU-powered algorithms integrated in Memgraph. Includes centrality measures, link analysis and graph clusterings. |
| [distance_calculator](python/distance_calculator.py) | Python | Module for finding the geographical distance between two points defined with 'lng' and 'lat' coordinates. |
| [export_util](python/export_util.py) | Python | A module for exporting the graph database in different formats (JSON). |
| [graph_analyzer](python/graph_analyzer.py) | Python | This Graph Analyzer query module offers insights about the stored graph or a subgraph. |
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