![]() ![]() That’s why you will find lots of information about it. Nvidia GPU has rather good cost-performance and rather lower entry price, etc. Surely you may pay money so you can use GPU on the cloud server, but you could also want to have your own machine to do the proof of concept or smaller computing before you send it to cloud server. You can install tensorflow without GPU as starting point to learn, however you will find that it takes too long to finish the computing, and then you want to use a machine with GPU or other HW acceleration. There are some theories that have been there for 10s of years, however, due to slow CPU and limited data, they won’t be as useful today. Some scientists might say that there is nothing new in this AI revolution. GPU is one of the key components of this revolution that it can do without. That’s what I want to address this issue! Why GPU? However, it seems none of those have wider enough coverage. There are good articles, and I learn from those, too. I found there are so many documents around explaining how to install Tensorflow-GPU on Ubuntu. However, Deep Learning/Machine Learning is changing the world in such a different way! ![]() It’s definitely more beautiful, faster and more convenient for us. ![]() If you just want to know all the steps, you can skip to the section “Summary of steps”.ĭeep Learning / Machine Learning is a big revolution in the computing world! The software today has not really changed too much compared to 10 years ago in it’s underlying design. ![]() The following steps also work for Ubuntu 19.04 with some tweak. Then how you install Nvidia driver and Tensorflow with GPU acceleration back-end on Ubuntu 18.04 LTS. I will share the background of GPU and Deep Learning. * Install tensorflow-gpu 1.12/1.13/2.x on the same machine. * Apr 29, 2019: updated for Tensorflow 1.13 released. Install Tensorflow-GPU to use Nvidia GPU using anaconda on Ubuntu 18.04 / 19.04 do AI! ![]()
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