Installing the toolkit is pretty straightforward, and it listed on the download page as well: It will probably work just fine, but I prefer this approach. The deb (local) will download everything upfront, and then you have to install another patch. In case Nvidia decides to release updates to the toolkit, I hope this approach will make it easier to get them.

I choose the deb (network) installer since it is the smallest to download and it will configure APT repositories for you. DownloadingĪfter that, I headed to the CUDA Toolkit download page and make the following choices: I choose Ubuntu 16.04 since it is an LTS release, which means it will still receive security patches, and since it is officially supported by NVIDIA. Since I have had good experiences with Ubuntu, and the machine had an old version of Ubuntu installed, I upgraded that to the latest Long Term Support (LTS) release: 16.04.2 at the time of writing. Preparationsīefore even thinking of installing something, I had to make sure my machine was running a supported operating system. If you’re up for a journey, continue reading…. Luckily, NVIDIA distributes the CUDA toolkit which lets you do that. Only problem is: you can’t write arbitrary code and just run it on a graphics card. Sure, it isn’t a high-end card for todays standards, but at least it might be fun to try it. To give my old workstation annex gaming PC a new meaning in life, why not try to employ its NVIDIA GT218 for some experiments? When I was at university, I followed some courses and specialisations in this field, but then during my career I hardly ever used any of it.īack in those years, complex neural nets and genetic algorithms took days to build, mainly because we didn’t have the computing power for that.īut nowadays, things have changed, and such models can relatively quickly be built using a commodity graphics card. Lately, my interest for machine learning and artificial intelligence has revived.

How to install cuda on ubuntu 16.04