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cuGraph - RAPIDS Graph Analytics Library
https://web.archive.org/web/20081031230449id_/http://www.ii.uib.no/~fredrikm/fredrik/papers/CP75.pdf defines a parallel implementation of the weighted matching problem. Create an MNMG C++ implementation that approximates the solution of the weighted matching problem.
Our current shortest path implementation uses delta stepping to parallelize Dijkstra's algorithm efficiently on the GPU. Dijkstra's algorithm requires all edges to have positive weights. In order to support weight...
This PR adds a scheduler plugin that shutdowns the cluster when one or multiple workers crash.
Implement Local Clustering Coefficient algorithm.
We have a prototype code that was written by an intern a couple of years ago. Use the prototype to construct an algorithm to implement overlapping community detection within the...
Compute shortest paths using Bellman-Ford algorithm.
### How would you describe the priority of this documentation request Medium ### Describe the future/missing documentation Explaining the process to future cuGraph developers both in-house and in networkX community...
Implement C API for biased sampling including C API tests.
Implement biased sampling using the biased sampling primitive. The public biased sampling function takes bias values as edge property values; otherwise same to the uniform neighbor sampling function. Closes #4290
