Or run heavy renders of complex ray-traced scenes.

Or do heavy 3D reconstruction from 2D images.

Or run Monte-Carlo simulations to compute complex likelihoods on parametric trading models.

Or train ML models.

The list of things you can do with a computer with many, many cores is long, and some of these (or parts thereof) are sometimes rather annoying to map to a GPU.

‘Rather annoying’ certainly doesn’t have to be a problem. Apple can afford to pay engineers lots of money to write libraries that do that for you.

The only problem I see is that Apple might (and likely will) disagree with some of their potential customers about what functionality is essential.

While working in rust I am most limited by single core performance. Incremental builds at the moment are like, 300ms compiling and 2 seconds linking. In release mode linking takes 10+ seconds with LTO turned on. The linker is entirely single threaded.

Fast cold compiles are nice, but I do that far more rarely than incremental debug builds. And there’s faster linkers (like mold[1] or lld) but lld doesn’t support macos properly and mold doesn’t support macos at all.

I’m pretty sure tsc and most javascript bundlers are also single threaded.

I wish software people cared anywhere near as much about performance as hardware engineers do. Until then, single core performance numbers will continue to matter for me.

[1] https://github.com/rui314/mold

The same machine does nychthemeral builds that include macOS compiles on a QEMU VM, but given that I'm asleep when that happens, I only care that the night's work is done before I get up.

[0] https://ardour.org/

The speed record for building my software is held by a system with over 1k cores (a couple of seconds, compared to multiple minutes on a mid-size Threadripper).

  add(1, 1) = 2
  add(1, 2) = 3
  add(1, 3) = 4
  add(1, 4) = 5
  ...

For example, make -j 10, or mvn -T 10.