PAPPP

…I probably should have checked the byline before posting. It does still come from the same material, just a little more directly.

There’s some weirdness on that because she did some important but not-very-public work at IBM in the 60s with their ACS/“Project Y” effort that did what we later call superscalar/multi-issue processors like …20 years before those terms existed. As part of that she wrote a paper about “Dynamic Instruction Scheduling” in 1966 under her pre-transition identity that is a like retroactive first cause for a bunch of computer architecture ideas.

There was almost nothing about that work in public until Mark Smotherman was doing some history of computing work in the late 90s, put out a call for information about it, and she produced a huge trove of insider information after deciding it was worth exposing the provenance. There’s a neat long-form LATimes piece about the situation which is probably the primary source for the history in OP’s link.

Neat.

I set up some basic compute stuff with the ROCm stack on a 6900HX-based mini computer the other week (mostly to see if it was possible as there are some image processing workloads a colleague was hoping to accelerate on a similar host) and noticed that the docs occasionally pretend you could use GTT dynamicly allocated memory for compute tasks, but there was no evidence of it ever having worked for anyone.

That machine had flexible firmware and 64GB of RAM stuffed in it so I just shuffled the boot time allocation in the EFI to give 8GB to the GPU to make it work, but it’s not elegant.

It’s also pretty clumsy to actually make things run, lot of “set the magic environment variable because the tool chain will mis-detect the architecture of your unsupported card” and “Inject this wall of text into your CMake list to override libraries with our cooked versions” to make things work. Then it performs like an old GTX1060, which is on one hand impressive for an integrated part in a fairly low wattage machine, and on the other hand is competing with a low-mid range card from 2016.

Pretty on brand really, they’ve been fucking up their compute stack since before any other vendor was doing the GPGPU thing (abandoning CTM for Stream in like a year).

I think the OpenMP situation was the least jank of the ways I tried getting something to offload on an APU, but it was also one of the later attempts so maybe I was just getting used to it’s shit.

Don’t trust that they’re 100% compatible with mainline Linux, ChromeOS carries some weird patches and proprietary stuff up-stack.

I have a little Dell Chromebook 11 3189 that I did the Mr.Chromebox Coreboot + Linux thing on, a couple years ago I couldn’t get the (weird i2c) input devices to work right, that has since been fixed in upstream coreboot tables and/or Linux but (as of a couple months ago) still don’t play nice with smaller alternative OSes like NetBSD or a Haiku nightly.

The Audio situation is technically functional but still a little rough, the way the codec in bay/cherry trail devices is half chipset half external occasionally leads to the audio configuration crapping itself in ways that take some patience and/or expertise to deal with (Why do I suddenly have 20 inoperable sound cards in my pulse audio settings?).

This particular machine also does some goofy bullshit with 2 IMUs in the halves instead of a fold-back sensor, so the rotation/folding stuff via iio sensors is a little quirky.

But, they absolutely are fun, cheap hacker toys that are generally easy targets.

You can still readily get crank hand drills, I have a (vaguely) modern one that I use for situations where I want the control/tactile feedback and/or have restricted access or the like. It covers a different set of problems than the standard cordless.

Mine is Fiskars branded and a little plasticky (and not the version they sell currently). I like it enough that I’ll get a nicer one if I kill it.