EDIT: there is more discussion going on at /r/MachineLearning than here: https://www.reddit.com/r/MachineLearning/comments/6kv3rs/mop...
[0] http://i.imgur.com/twhTpcC.jpg
[1] http://i.imgur.com/1peXVnq.png
[3] tldr: 16 GByte HBM2, 25 TFlop FP16, ~1000-1500 dollar.
[4] https://www.newegg.com/Product/Product.aspx?Item=N82E1681410...
Using OpenCL code with batch size which favors one or the the other is enough to cause this (and much) higher delta.
DeepBench isn't a benchmark, it's a benchmarking tool overall there is very little chance that given the current state of NVIDIAs BLAST libraries and the rest of their eco system that Vega is going to be beating it's hardware.
Weird website, took me a while to classify its purpose. So, is this like an AMD version of NVIDIA's CuDNN? Can we run TensorFlow on AMD GPUs?
It seems at the moment only Caffe is public and it's a port of the CUDA version to OpenCL [0][1] to allow it to run on AMD GPUs like the recently released AMD Vega Frontier Edition. From the wording on the page it looks like it could be an equivalent to CuDNN.
[0] through AMDs tool called HIP which can convert CUDA