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The Raspberry Pi results are really cool to see. Sure, for a highly-tuned library like cuDNN the existing operators might be close to as fast as you can get, bu
by loser777 9y ago
The Raspberry Pi results are really cool to see. Sure, for a highly-tuned library like cuDNN the existing operators might be close to as fast as you can get, but it's unlikely that every platform where it may be interesting to deploy a deep learning model can get the same amount of attention. I hope that these results mean that in many cases we can get highly optimized implementations without exhaustive manual effort.
- dr_zoidberg 9y agoUp until recently at work I had to work with Keras on CPU-only and the easiest way to get things working was TensorFlow backend. Earlier this year the 1.3 update gave me roughly 15% performance increase just from pip install tensorflow --upgrade Fortunately I got a new machine with a cuDNN capable GPU, but I'll be testing the NNVM for Keras backend when its working. We might get to squeeze some epochs out of my old machine, now in the hands of a secretary who won't really notice we're training a net while he replies some emails.