I thought the RTX would do better here, but the Ryzen 3750h performs better on training a model in tensorflow. I'm using this guide to get things going, and I'm usng tf-nightly with Ubuntu 20.04.<p>https://www.tensorflow.org/tutorials/quickstart/beginner<p>I'm wondering if using nvidia 440 drivers is the reason? I also have 3 versions of CUDA installed (10.0, 10.1, and 10.2). The tensorflow-js test I did uses CUDA 10.0, and the Ryzen performs roughly 50% faster. The Python test I did uses CUDA 10.1, and the CPU is less than 10% faster.<p>Even so, shouldn't the GPU perform an order of magnitude better here? I feel like I must be doing something wrong :/
The network that you train in that tutorial is quite small. Your networks have to get quite large before the overhead of transferring the network onto the GPU is negligible to the cost of training it. You'll see the benefit of the GPU with larger models.
I think my calculations are correct here<p><pre><code> Model Zen+ 2060
Cores 4 1920
Threads 8 1920
Cycles 2.3 1.365
FP64 GFLOPS 2944 163
FP32 GFLOPS 5888 5242
FP16 GFLOPS 11776 10483
</code></pre>
So it would kind of make sense yeah. 2060 isn't that strong.<p>But note: I'm not totally sure on the Zen+ theoretical speeds