ResNeXt.pytorch
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Sublinear speed-up with dataparallel
With default arguments apart from cardinality (set to 16), I get:
On 1 1080 ti with minibatch size 20: ~9 minutes per epoch. Using dataparallel across 4 1080 ti's with minibatch size 128: ~4.5 minutes per epoch.
Perfect linear scaling would give you 2.25 minutes per epoch. Any idea what's going on here/how to get better scaling?
Hi!
Have you tried with a vanilla resnet? to check whether the problem is in the model or the dataloader?
Pau