Yeah, I'm retired. The only person I have to answer to regarding progress is me. I'm a stubborn son of a bitch when it comes to choosing quality over speed...
That doesn't mean I don't like progress mind :) This morning I got the preliminary results of a 'C' front-end to the compiler (it uses clang to compile to LLVM IR, then translates to our IR, then feeds that IR into the autovectoriser as if it had parsed the code itself). So for the exact same source code I now have:
┌─────────────┬────────────┬──────────────────────┬──────────┐
│ Benchmark │ clang -O2 │ xcc --par-auto (GPU) │ Speed-up │
├─────────────┼────────────┼──────────────────────┼──────────┤
│ saxpy │ 1,546 µs │ 726 µs │ 2.1× │
├─────────────┼────────────┼──────────────────────┼──────────┤
│ Mandelbrot │ 394,238 µs │ 2,110 µs │ 187× │
├─────────────┼────────────┼──────────────────────┼──────────┤
│ nbody │ 37,090 µs │ 1,035 µs │ 36× │
├─────────────┼────────────┼──────────────────────┼──────────┤
│ perlin │ 78,016 µs │ 1,850 µs │ 42× │
├─────────────┼────────────┼──────────────────────┼──────────┤
│ mandel_deep │ 73.2 s │ 55.8 ms │ 1,312× │
└─────────────┴────────────┴──────────────────────┴──────────┘
Those are some pretty fine speedups, from naive C, with no alterations from the standard "C" code - it automatically finds places that can be made data-parallel, tracks the data-hazards to make sure its safe to "GPU" and writes all the kernels, boilerplate and data-stream-management if necessary. Obviously the checksums have to match, so I know it did the work correctly too :)Hacker News isn't interested - any post I make linking to the webpages is immediately blocked/dead so I'll wait until the C++ front-end is ready (some time next week) and announce it somewhere else. A compiler that takes standard C/C++ code and speeds it up by automatically finding data-parallel areas and scheduling them on the GPU with no programming overhead is pretty rare.
Oh, and it manages the local network as well, so you can run xcd on machines on your lan, or via the TB4/5 bridge between Macs and it'll schedule on other GPUs, just like it manages multiple GPUs on the local machine. It characterises both latency and compute-time to figure out which devices are worth scheduling on.
Awesome, this is genuinely-cool HN material. Thanks for sharing.
So, the real input to your autovectorizer is LLVM IR; you could soon enough support any language that has an LLVM front-end? (I say soon enough instead of immediately because I’m sure there’s some manual wiring up to do). That seems like a pretty big deal. Do Fortran next, pls. :)
Hell yea I love that computers are getting another chance at becoming compute fabric, just using each others GPUs. Sick.
sounds very cool - is this basically "C" support for cuTile? :)
> Hacker News isn't interested
I wouldn't be too sure about that :)
That is pretty adventurous, but it sounds really cool! Will it be open source?
I like it! The Rust crew would love this I bet.
After asking my LLM some questions to barely grasp what you are working on, I can now say: very cool!
For anyone wondering, the thing lives at https://compile-xc.org/ ;)