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As the network size is proportional to the dataset size, and the GPU memory is limited, some parallelism has to be implemented.
A naive approach is to split the dataset into possibly-overlapped windows to be processed separately and then the results are merged. This can be done sequentially (as in this repo) or with a DataParallel strategy.
On the other hand, in order to process all the data at once, one might want to adopt a ModelParallel strategy.
The text was updated successfully, but these errors were encountered:
Thanks for your comment! Indeed, the README needs to be updated, sorry for the delay.
You can find that file in datasets/hyperbolic3d/. We provide you with the original data volume, and two different decimations.
Let me know if you need any help. I would ask you to open a new issue, as this thread is dedicated to the parallelism.
As the network size is proportional to the dataset size, and the GPU memory is limited, some parallelism has to be implemented.
A naive approach is to split the dataset into possibly-overlapped windows to be processed separately and then the results are merged. This can be done sequentially (as in this repo) or with a DataParallel strategy.
On the other hand, in order to process all the data at once, one might want to adopt a ModelParallel strategy.
The text was updated successfully, but these errors were encountered: