( Compute Capabilities version identify the features supported my the GPU.) GPU card with CUDA Compute Capabilities 3.0 or higher.NVIDIA driver associated with CUDA Toolkit 8.0.Here are a summary of those system requirements and steps: To use GPU-powered TensorFlow on your Mac, there are multiple system requirements and libraries to install. My Mac had a NVIDIA video card so, I was up for local adventures too! It was awesome to see this development and the application of these platforms to Deep Learning. During that process, I read a bit about GPUs, CUDA and cuDNN. The only problem I encounter was to update the NVIDIA driver, and it was done easy. It was not a painful experience(as I was expecting) to use this hardware because Udacity provided an AIM with the necessary software already installed, and I didn’t need to install anything else.
As part of the Udacity’s Self-Driving Car Nanodegree, I had the opportunity to try a GPU-powered server for Traffic Sign Classifier and the Behavioral Cloning projects in Term 1.
