Optimized pillow-simd needed to leverage new GPU instances
@rosbo is already working on this.
Since Aug 14, 2018.
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Description
(Copied from https://www.kaggle.com/dansbecker/running-kaggle-kernels-with-a-gpu/code#328307 as requested by @sebbov ).
With the limited CPU available, being able to quickly read and manipulate images is important. Can I suggest you install pillow-simd with an optimized jpeg library? It will reduce CPU use by around 2-4x when training models, which will dramatically increase the utility of these new instances. The step by step instructions for installing it have been kindly provided by Soumith Chintala here (note that without these exact steps pillow-simd will not use libjpeg-turbo, even if you have it installed as your system libjpeg):
https://gist.github.com/soumith/01da3874bf014d8a8c53406c2b95d56b
I'm not familiar enough with docker to know what PR to send in exactly - hopefully this is enough info for the in-house experts to set it up.
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