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[QST]: Steiner tree algorithm
What is your question?
HI, I understand that cuGraph does not support the Steiner algorithm. I have a directed and unweighted graph that I need to analyze using a Steiner tree. The graph is too large (26GB) to run on NetworkX without GPU support. What alternative way would be there to implement the Steiner tree with GPU acceleration? I'm also open to other suggestions. Thank you!
Code of Conduct
- [X] I agree to follow cuGraph's Code of Conduct
- [X] I have searched the open issues and have found no duplicates for this question
Hi Stephanie, You might run a minimum spanning tree instead. If every vertex is a Steiner terminal, the MST corresponds to the Steiner tree. First you will need to convert your graph to undirected, since directed graphs aren't supported for MST or Steiner. You might also try NetworkX with GPU backend, which is now available on pip and conda.
On Thu, May 23, 2024 at 4:16 PM Stephanie Won @.***> wrote:
What is your question?
HI, I understand that cuGraph does not support the Steiner algorithm. I have a directed and unweighted graph that I need to analyze using a Steiner tree. The graph is too large (26GB) to run on NetworkX without GPU support. What alternative way would be there to implement the Steiner tree with GPU acceleration? I'm also open to other suggestions. Thank you! Code of Conduct
- I agree to follow cuGraph's Code of Conduct
- I have searched the open issues https://github.com/rapidsai/cugraph/issues and have found no duplicates for this question
— Reply to this email directly, view it on GitHub https://github.com/rapidsai/cugraph/issues/4439, or unsubscribe https://github.com/notifications/unsubscribe-auth/ACN2STUV3N4NK2Y4YWFDMVLZDZMBZAVCNFSM6AAAAABIGNAO7OVHI2DSMVQWIX3LMV43ASLTON2WKOZSGMYTGOBVG43DEOA . You are receiving this because you are subscribed to this thread.Message ID: @.***>
Was @jeaton32's answer sufficient? Working through some old issues, I would love to close this. If it wasn't sufficient, please let us know what would be helpful and we can add it to our backlog.
