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In current implementations, we suppose that all data fit in GPU memory. How to handle really huge graphs? Try to implement a multi-GPU solution for graphs which cannot be fully stored in RAM. It should be possible to utilize classical solutions for distributed huge matrices multiplication.
The text was updated successfully, but these errors were encountered:
In current implementations, we suppose that all data fit in GPU memory. How to handle really huge graphs? Try to implement a multi-GPU solution for graphs which cannot be fully stored in RAM. It should be possible to utilize classical solutions for distributed huge matrices multiplication.
The text was updated successfully, but these errors were encountered: