Re:Why is so much memory needed for deep neural networks?
by taeric on Thursday March 23, 2017 @09:33AM
(#13939538)
Apologies, I did not mean to say that the information was not in the article. It mostly was. (I think the only thing missing is that you are saying that of that 168 megs, 104 are the weights and 64 are the activations. This gives 64 * 32 for the 2G of memory. Right?)
The difficulty for me is merely in visualizing.
And I should have said that I was not looking for a single answer on whether GPUs make sense in predicting. A chart with rough guidance on when you will target specific execution environments is all I'm hunting for. My bias is that lower power targets are more common. Phones and the like. But, I would not be willing to bet heavily on that.
The difficulty for me is merely in visualizing.
And I should have said that I was not looking for a single answer on whether GPUs make sense in predicting. A chart with rough guidance on when you will target specific execution environments is all I'm hunting for. My bias is that lower power targets are more common. Phones and the like. But, I would not be willing to bet heavily on that.