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I followed this tutorial and installed tf-gpu using conda (https://www.pugetsystems.com/labs/hpc/The-Best-Way-to-Install-TensorFlow-with-GPU-Support-on-Windows-10-Without-Installing-CUDA-1187/) and it worked because I am seeing "...gpu:0" in my printed out log. Before I did the installation, I already have CUDA driver installed, so I am not sure.

Seems to me that conda install tensorflow-gpu comes with cuda toolkit and cuDNN,etc. I was wondering if installing CUDA driver is a require step. Another post I found did't mention driver either (https://towardsdatascience.com/tensorflow-gpu-installation-made-easy-use-conda-instead-of-pip-52e5249374bc). But the official GPU guide says it's required, so I am confused. I am doing it on Windows 10.

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    in my experience on linux, conda install cuda does not install a GPU driver. and a GPU driver is required to use a CUDA GPU. On windows, in many cases a GPU driver will be automatically installed by windows, e.g. for typical WDDM GPUs like GeForce GPUs. Whether or not this driver is compatible with the toolkit version installed by conda is perhaps not guaranteed, but I think it generally would be compatible. Nov 14, 2018 at 2:48

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In my experience you do not need to install cuda or cudnn. Just your graphics driver is enough.

But depending on your system it might not be optimized. For that you would need to compile tensorflow from scratch and optimize it for your system.

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Depends on the machine you are running on. For example, you can configure a Google Deep Learning VM to install the NVIDIA driver on startup.

If the driver is not installed, then follow the Tensorflow instructions on how to install the NVIDIA driver. Here are the instructions for Linux. Note that you only need to install the driver, and not the toolkit.

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