Can Caffe or Caffe2 be given input data directly from gpu?

Question

I\'ve read caffe2 tutorials and tried pre-trained models. I knew caffe2 will leverge GPU to run the model/net. But the input data seems always be given from CPU(ie. Host) memory

Answer 1

As you've noted, using a Python layer forces data in and out of the GPU, and this can cause a huge hit to performance. This is true not just for Caffe, but for other frameworks too. To elaborate on Shai's answer, you could look at this step-by-step tutorial on adding C++ layers to Caffe. The example given should touch on most issues dealing with layer implementation. Disclosure: I am the author.

Answer 2

I don't think you can do it in caffe with python interface.
But I think that it can be accomplished using the c++: In c++ you have access to the Blob's mutable_gpu_data(). You may write code that run on device and "fill" the input Blob's mutable_gpu_data() directly from gpu. Once you made this update, caffe should be able to continue its net->forward() from there.

UPDATE
On Sep 19th, 2017 PR #5904 was merged into master. This PR exposes GPU pointers of blobs via the python interface.
You may access blob._gpu_data_ptr and blob._gpu_diff_ptr directly from python at your own risk.