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Adept II

Machine Learning Library Support

Last week when Tesla announced that all production cars now come standard with an Nvidia Drive PX 2 system, Elon Musk said that it was a "tight call" with AMD in regards to who had the better deep learning hardware.  This is a field I am very interested in and it has been dominated by Nvidia.  The four major tool-kits for deep neural network (DNN) machine learning are TensorFlow by Google, Caffe, CNTK by Microsoft, and Torch.  Unfortunately, none of these run OpenCL without third party modifications, which are not officially supported.  My question is what is AMD going to do about this?  Tesla obviously tested something and found it to be close to Nvidia's capabilities.  However, there is currently no mainstream option.  Is OpenCL not the answer?  Are HIP or the HCCompiler the answer?  Right now, anybody interested in developing a world class machine learning algorithm has no choice but to do so on Nvidia hardware with CUDA.  Serious support of one or more of these tool-kits would be helpful. 

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Adept II

AFAIK AMD do have a machine learning projects running.

  1. Caffe OpenCL GitHub - BVLC/caffe at opencl

The following work seems to not be official. But the maintainer seems to be AMD related.

  1. DeepCL GitHub - hughperkins/DeepCL: OpenCL library to train deep convolutional neural networks
  2. cltorch GitHub - hughperkins/cltorch: An OpenCL backend for torch.

hughperkins is also working on tensorflow with OpenCL.

HIP might help since it can convert CUDA code into HIP code. But , It's a pain to setup and only supports Linux. I'm still trying to setup ROCm on my GTX 970/Manjaro Linux box so I could compare the performance of HIP vs CUDA (I'm working on a GPU ray tracer).

BTW, definitely agree that AMD have to do more work on ML.