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Enhance data loading and transformation performance #68

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cwerner opened this issue Dec 9, 2021 · 0 comments

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cleanup performance

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cwerner commented Dec 9, 2021

The data loaders most likely are pretty inefficient at the moment. Let's try to profile and optimise GPU utilisation.

Potential problems atm:

data is concatenated from potentially many data loaders into a big batch
distmap (for boundary loss) is calculated in the data loader
one hot encoded representations are created multiple times
tensors are potentially moved from gpu to cpu and back multiple times (plus some bumpy operations)

cwerner added cleanup performance labels

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