Phoronix: NVIDIA GeForce RTX 2070 OpenCL, CUDA, TensorFlow GPU Compute Benchmarks
Here are the first of our benchmarks for the GeForce RTX 2070 graphics card that launched this week. In our inaugural Ubuntu Linux benchmarking with the GeForce RTX 2070 is a look at the OpenCL / CUDA GPU computing performance including with TensorFlow and various models being tested on the GPU. The benchmarks are compared to an assortment of available graphics cards and also include metrics for power consumption, performance-per-Watt, and performance-per-dollar.
http://www.phoronix.com/vr.php?view=26984
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NVIDIA GeForce RTX 2070 OpenCL, CUDA, TensorFlow GPU Compute Benchmarks
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NVIDIA GeForce RTX 2070 OpenCL, CUDA, TensorFlow GPU Compute Benchmarks
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Originally posted by artivision View Post
https://devblogs.nvidia.com/nvidia-t...ture-in-depth/
https://en.wikipedia.org/wiki/List_o...ce_10_series_2
I asked a legitimate question and don't have a clear answer.
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Originally posted by eydee View PostCheapest one I can find locally is 660€ with no warranty. Fuck nvidia and its prices.
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Cheapest one I can find locally is 660€ with no warranty. Fuck nvidia and its prices.
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I'm glad that you included the GTX980
Originally posted by artivision View PostAlso if Nvidia wants they can flash Gtx1000 with the Pro firmware and deploy FP16 2x there too.
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Guest repliedAwesome, now all of the dozen or so people who really need to do ML for a living, will have a GPU to buy.
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Is my understanding correct if I say that the Tensorflow benchmarks all focus on the the forward pass (at times also "inference") of a neural network? If so, is it possible to measure the backwards pass (backpropagation)? as well
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