Minimum required hardware component to install tensorflow-gpu in python

Question

I'm tried many PC with different hardware capability to install tensorflow on gpu, they are either un-compatible or compatible but stuck in some point. I would like to know the minimum hardware required to install tensorflow-gpu. And also I would like to ask about some hardware, Is they are allowed or not: Can I use core i5 instead of core i7 ?? Is 4 GB gpu enough for training the dataset?? Is 8 GB ram enough for training and evaluating the dataset ?? with most thanks.

Answer 1

TensorFlow (TF) GPU 1.6 and above requires cuda compute capability (ccc) of 3.5 or higher and requires AVX instruction support.
https://www.tensorflow.org/install/gpu#hardware_requirements .https://www.tensorflow.org/install/pip#hardware-requirements .

Therefore you would want to buy a graphics card that has ccc above 3.5. Here's a link that shows ccc for various nvidia graphic cards https://developer.nvidia.com/cuda-gpus .

However if your cuda compute capability is below 3.5 you have to compile TF from sources yourself. This procedure may or may not work depending on the build flags you choose while compiling and is not straightforward. In my humble opinion, The simplest way is to use TF-GPU pre-built binaries to install TF GPU.

To answer your questions. Yes you can use TF comfortably on i5 with 4gb of graphics card and 8gb ram. The training time may take longer though, depending on task at hand.

In summary, the main hardware requirement to install TF GPU is getting a Nvidia graphics card with cuda compute capability more than 3.5, more the merrier. Note that TF officially supports only NVIDIA graphics card.

Answer 2

You should find your answers here:

https://www.nvidia.com/en-gb/data-center/gpu-accelerated-applications/tensorflow/

From the link:

The GPU-enabled version of TensorFlow has the following requirements:

• 64-bit Linux
• Python 2.7
• CUDA 7.5 (CUDA 8.0 required for Pascal GPUs)
• cuDNN v5.1 (cuDNN v6 if on TF v1.3)