I've got an HP Z640 workstation with dual E5-2690 v4's and it is basically silent under full load. It has no problem running all 28 cores at 3.2GHz which is the max all-core speed for that processor.
Really curious. I deploy code to a large production server cluster, my friends in academia submit code to large scientific computing clusters, but I don't know of anyone with this much power in their own desktop. I guess I've been in video edit suites with machines much more powerful than the average PC, but not this crazy.
Running inadequate machines waste time of otherwise expensive engineers. The other day I was giving a live demo of an interception proxy and accidentally clicked on a very large HTTP response. The machine I was using only had 32 GB of RAM so I had to open task manager and kill the app so I could re-start it because the meeting would have been over by the time it loaded due to disk caching.
As a remote employee it allows me to most of my development locally, and then use larger environments for a shorter period of time later on.
Combine 3 or 4 of them, and I can have an actual cloud running under my desk, for testing things like kubernetes deployments, with enough capacity for a few concurrent test environments.
As I said above they run basically silent, so I can use them in a shared office space without annoying my neighbors.
I've been hearing of people buying Mac Pros for cloud demos so they can run VMs on them locally because they're among the most compact, compute and memory dense systems you can buy.
I had access to racks of hardware to do a lot of testing but they were in Colorado, while I am in EU which made latency a real problem.
A lot of battle-tested engineering software doesn't do distributed-memory parallelism well. I've personally used MCNP and GEANT4 (particle physics software) on a 48 core, 1 TB RAM workstation. It's interesting browsing the web while the computer is running gigantic calculations in the background on two [physical] CPUs, hooray for the process scheduler doing a good job.
Imagine doing web dev in a language where you refresh the webpage to see if it worked vs having to run a long build. The former is better, even though it's not really as good as careful reading of your changes, but there are many times throughout the day when you just want the compiler to bark at you to clear any stupid type or syntax errors. The faster your machine and more parallel the build, the closer you get to that web dev experience.
It's funny the things that need a lot of beans to run; I was sitting with one of the GIS guys and he just clicked a button which then caused all 24 cores on his rig to flatline for about 4 minutes. The end result? A map of our city suddenly had a few boxes drawn over the top of it. As it turns out he was pulling in data from half a dozen sources to map out areas where there was government run housing that experienced higher than average levels of emergency services call outs. Apparently, in the past doing that manually would probably have taken several people about a week to do and wouldn't have been as accurate.
Having access to machines remotely can replace some of that, but it definitely costs time.
Basically 3D rendering.
Edit: I guess I should be clear and say that the simulations themselves are running on a commercial software package (Fortran based) and I'm simply setting them up, spinning them off, and then processing all of the resulting data in Python.