When I use the pytorch compiled from the src(pytorch-src), the CPU usage is much higher than the pytorch installed directly through conda(pytorch-conda).
In addition, when using pytorch-src, gpu usage is lower than pytorch-conda.
I just followed the instructions on github to install from src. I’m using python 2.7. Is there anything with my installation?
You can check if cudnn is being used by typing torch.backends.cudnn.is_acceptable(torch.cuda.FloatTensor(1)) in your python interpreter.
For checking if the library was linked against OpenBlas or MKL, type ldd libTH.so, where libTH.so is the library file that was compiled.
Check this thread, the discussion provides some details on blas and torch and some additional settings and flags you can look into. Maybe run the scripts I provided there so we can see if it’s indeed a blas-related issue? Also posting the compilation logs could help if you indeed see performance differences between the two installs.