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happy233cat avatar happy233cat commented on August 17, 2024

Hi, Jeffery

did you find the code for learning-based graph partitioner? I am also looking for it

Thanks!

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molamooo avatar molamooo commented on August 17, 2024

Sorry I didn't find related codes. But I found this self hosted dataset. Not sure if it's preprocessed by the learning-based partitioner. link

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happy233cat avatar happy233cat commented on August 17, 2024

Got it, That's super helpful!
did you manage to compile the whole project to generate the gnn executable?
I was encountering some compilation errors

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molamooo avatar molamooo commented on August 17, 2024

I was able to compile and run the project with no issue.

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happy233cat avatar happy233cat commented on August 17, 2024

which version of cuda you are using? I am currently using CUDA 11.0 for ampere GPU

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molamooo avatar molamooo commented on August 17, 2024

It's been a long time... I think I run it using CUDA 10.2/10.1 for volta GPU.

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happy233cat avatar happy233cat commented on August 17, 2024

Got it, I will try with CUDA 10.1/10.2, there are some issue with compilation on CUDA-11

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happy233cat avatar happy233cat commented on August 17, 2024

Just successfully compile it with CUDA 10.2.
It seems that the current version just simply partition the graph by the range of rows?
also do you know is there any converter to generate the inputs for ROC like reddit-dgl?

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molamooo avatar molamooo commented on August 17, 2024

It seems that the current version just simply partition the graph by the range of rows?

Yeah I think so.

also do you know is there any converter to generate the inputs for ROC like reddit-dgl?

I read through the code of loading dataset in ROC, the format should be a simple CSC graph with indptr & indices concatenated together. It's not hard to generate a dataset by yourself, but I think the performance won't be acceptable since there is no learned-based partitioner.

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