skip0110

AFIK it’s only NVIDIA that allows containers shared access to a GPU on the host.

With the majority of code being deployed in containers, you end up locked into the NVIDIA ecosystem even if you use OpenCL. So I guess people just use CUDA since they are limited by the container requirement anyways.

That’s from my experience using OpenGL headless. If I’m wrong please correct me; I’d prefer being GPU agnostic.

I bet the people you work with are very happy to have you as a lead.

I’ve been in this scenario and I didn’t wait for layoffs. I left and applied my skills where shit code is not tolerated, and quality is rewarded.

But in this hypothetical, we got this shit code not by management encouraging the right behavior, and giving time to make it right. They’re going to keep the yes men and fire the “unproductive” ones (and I know fully, adding to the pile is not, in the long run, productive, but what does the management overseeing this mess think?)

They were just trying to make us smarter.

https://studyfinds.org/chewing-on-wood-brain-function-memory/

[kidding]

To be fair, if you give me a shit code base and expect me to add features with no time to fix the existing ones, I will also just add more shit on the pile. Because obviously that’s how you want your codebase to look.