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I'm looking to build a PC for deep learning.

Will TensorFlow work on an AMD GPU with the same speed as on Nvidia ones? I am asking this because AMD doesn't have tensor cores or CUDA cores, but it will have 16gb of High Bandwidth Memory VRAM.

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Tensorflow only works with Nvidia gpus. There are solutions that allegedly also work with AMD, but it is certainly easier to set up the original cuda variant.

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It is difficult to make a broad statement about which hardware acceleration product has the best performance for deep learning until some comparative metrics using the same algorithms and data sets are published, which requires the availability of both products. It's anyone's guess from the below spec comparison. The information on the net is and could only be conjecture at this point.

    AMD Radeon VII
    Vega 20 GPU
    16 GB HBM2 memory
    1 Tb/s memory bandwidth
    60 compute units 
    3,840 GCN 1.8GHz stream processor cores 
    expected price $700 (possibly lower due to 7 nm lithography)
    software ecosystem set up difficulty: high

    NVidia RTX 2080 Ti
    GeForce RTX 2080 Ti GPU
    11 GB 352-Bit GDDR6
    14 GHz eff memory clock
    4,352 CUDA 1.5GHz stream processor cores
    PCIe 3.0
    current low side of newegg price $1,189
    software ecosystem set up difficulty: medium
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Tensorflow doesn't work on AMD GPUs afaik. Only Nvidia GPUs work flawlessly with these frameworks. I bet it's because of the CUDA environment built by NVidia. They have all the required ecosystem ready for ML/DL workloads.

You may want to explore Open CL in case you plan to do some uplifting with Radeon GPUs.

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