Puzzling phenomena
I am using Pytorch with the ‘fastai’ library supporting the deep learning course by the same name. I am using Ubuntu 16.04, a Titan V, and Anaconda 3.6.
Here is what puzzles me:
When I run the following code without any other  jobs running, it is significantly slower than when the GPU is running other process. (Specifically, it is under heavy load running crypto mining software.) I have repeated the trials numerous times to make sure that there were no differences in pre-computing or caching taking place. Moreover, I have tested this off and on over several weeks with the same result. I have used nvidia-smi to verifying what jobs are running on the GPU.  Here are the times:


Time with no load: 45 seconds


Time with load:      20 seconds


arch=resnet34 data = ImageClassifierData.from_paths(PATH, tfms=tfms_from_model(arch, sz)) learn = ConvLearner.pretrained(arch, data, precompute=True) learn.fit(0.01, 5)
This really doesn’t make sense to me.
I’ve searched around on this fourum and others and haven’t found out what might be taking place. I hope I haven’t made dumb mistake in my observations.
Thanks in advance for any thoughts.