I was reading the piece, waiting for the punchline of what kind of unholy beast of a workstation she was using, and wasn’t disappointed.
Thing is, physicists, heck, scientists in general, are not programmers. Fortran 77 and python are pretty much the only shows in town - and your usual data crunching script will be huge, procedural, in log time, and will eat mountains of memory while making disks thrash as hard as humanly possible.
For instance, I helped out a postdoc who I shared a lab with with his ephemeris calculator - it’d take in a series of fits images, and it’d tell you the ephemeris of whatever object you chose - by editing the source, and putting in the x/y of the object in the first frame.
Thing was, it took all night to do this for a single object from half a dozen frames. Most of the time was spent opening and closing each file to read each pixel, and then stuffing those pixels into a gigantic array, and writing that array to text files, and then re-reading those files, and then doing matrix multiplication and all sorts of amazingly baroque stuff that must have seemed like a good idea at the time. He was running it on a monster (for the time) of a workstation, with 64GB of ram and several TB of storage.
I banged together an app in C++ for him with a basic tcl/tk gui, and what had taken him a day of setup and a night of processing and an ungodly machine instead took about as long as it took for him to click on an object and click “go” - on my creaking laptop with 128mb of ram and a 1.4gb hard drive.
This was far from singular - after this, I found myself being “the guy” to talk to about your slow scripts - and that was basically every script in the department.
So no, not better, considerably worse, and I can’t help but think that having a more cross-disciplinary approach to science (embed tech people!) would yield benefits across the board.