We have already suffered it, let us save you a couple of days of desperation.

Tim Cook and Nvidia are going to go to hell for this — Myself after a lot of hours of fighting

At xplore.ai we are building Artificial Intelligence products using tailor-made algorithms. We create Deep Learning solutions to problems, mainly in the area of Computer Vision, for clients that hold large amounts of data and need a level of custom solutions further than what they can be provided from using already existing APIs. Our team’s main choice of local development hardware is Apple MacBooks, thus we mainly work on MacOS. Although we started training our Deep Learning models on the cloud (AWS), it became more and more expensive when our level of innovation increased. So we decided to build up our own high-end desktop machine, we call it Franky, where we would train large architectures or big Machine Learning models.

Training a GAN (Generative Adversarial Network) with a training set of 100.000 images with a single GPU can take various weeks

Franky: i7-7700K, 64Gb RAM, RTX 2080Ti

The main problem appeared when we started growing as a company, only one model could be train at once so there is now a queue of teammates waiting to train their own models for their own tasks. So we decided to investigate the possibility of providing a GPU to each data team member so they could use it with their own laptop. A GPU is normally attached to a motherboard, which is capable of handling such a monster (PCIe), which is inside a big case, which is not a laptop… but… welcome to the external GPUs world.

Thunderbolt 3: Taking USB-C ports to the next level

Taking into account that we already had available high-end GPUs our best option was Razer Core X, but you can select yours with the help of the great eGPU community. I’m not going to lie, we chose Core X because its powerful specs and, of course, for its slickly design. So far so good, it had not disappointed us, it has demonstrated to be a high-end tool and amazingly silent.

Note: the included Thunderbolt 3 cables with the Razer Core X are quite short (0.5m). Consider this and the fact that buying a 1m version can cost easily 40eur and we couldn’t find a 2m version suitable for our scenario.

So far everything looks fine: buy the case online, have it delivered in a few days (how nice it is to live in this world of popularized e-commerce), easily plug your graphics card and we are done 😊. Not so fast… this is only the beginning of our odyssey 😦.

Note: We work with CUDA software so AMD wasn’t an option. If you’re a lucky AMD user, you can close the post here and enjoy your new GPU, lucky you!

I’m sure you have heard about the ridiculous war between Nvidia and Apple which leaves us, the consumers, totally stranded. Nvidia no longer distributes official drivers to Apple MacOS is no longer officially compatible with Nvidia GPUs. So if you like to be up to date with the latest Apple software prepare to say good bye to Mojave and its very high-end dark mode technology because, at least, by the time I’m writing this, we need to downgrade to High Sierra.

Once we have our clean MacOS 10.13 ready to be eGPU boosted we need to start tricking the system, again the eGPU community will save our backs. You can follow the official Purge-Wrangler.sh guide here or continue to read because I’m going go through all the process as friendly as I can.