MIOpen

I agree with kbumsik here. AMD only has themselves to blame. They have great hardware and fantastic theoretical benchmarks. Heck, even their SGEMMs are really fast and in line with the 15TFlops of FP32 on the VEGA 64s that we've benchmarked. However, it comes down to software ecosystem and optimizations for common deep learning subroutines. MIOpen[1] is a step in this direction but still causes the VEGA 64 + MIOpen to be 60% of the performance of a 1080 Ti + CuDNN based on benchmarks we've conducted internally at Lambda. Let that soak in for a second: the VEGA 64 (15TFLOPS theoretical peak) is 0.6x of a 1080 Ti (11.3TFLOPS theoretical peak). MIOpen is very far behind CuDNN. Lisa Su, if you're reading this, please give the ROCm team more budget! 1. https://github.com/ROCmSoftwarePlatform/MIOpen

AMD already did. For example, their 3x3 convolution written in HSAIL is licensed under MIT and available here: https://github.com/ROCmSoftwarePlatform/MIOpen/blob/master/s...

This is great news. It’s extremely important to the research community that large companies enter into the DL silicon space to contend with NVIDIA’s monopoly. NVIDIA is now exerting pricing power to the point where they’ve decided to train their sales people to disregard the metric that is most important to customers: cost of training. Talk with one of their enterprise sales people and you’ll find they’ll say things like “FLOPS / $ doesn’t matter” to justify a 10x increase in price for their TESLA line. As history has shown, a monopolist sows the seeds of their own destruction and, by disregarding the metrics that matter, they alienate their customers. Here are open source projects that you can contribute to to break the monopoly: ROCm: https://rocm.github.io/ MIOpen: https://github.com/ROCmSoftwarePlatform/MIOpen TensorFlow: https://gith

MIOpen could be great one day. ATM you still get random problems like this: https://github.com/ROCmSoftwarePlatform/MIOpen/issues/19 That's an order of magnitude worse performance than NVidia on ResNet 52 for 2 months with no real reason. Great idea, but no one can use it reliably yet.