• @[email protected]English
    3•10 months ago

    Does it really make sense to have access to the entire C++ language to run on GPUs? Aren’t basic constructs that you take for granted in a complicated general purpose language like C++ super-expensive on a GPU? For example, my understanding is that whenever a GPU runs into a branch, it has to essentially run that part of the code twice: once for each branch.

    • AlmightySnoo 🐢🇮🇱🇺🇦
      2•10 months ago

      I don’t think their “entire C++ language” wording also includes the standard library (except maybe for algos with std::execution semantics). I’ve never written Vulkan code but I do a lot of CUDA (and now HIP) GPGPU stuff and things like template meta-programming are immensely useful to have generic kernels with stuff like compile-time strategy pattern to avoid lots of mostly duplicate kernels, unrolling and classical loop patterns like tiling etc… can be easily refactored into nice looking metafunctions with zero runtime overhead. It’s a game changer when you have access to modern C++ features to do GPU programming.

      • @[email protected]
        2•10 months ago

        I agree that having access to many of the compile time computation features could be nice, but the language also lets you do things like looping over pointers to objects with virtual methods that might not be resolvable until runtime, which I believe would be a performance killer.

  • AutoTL;DRBEnglish
    2•10 months ago

    This is the best summary I could come up with:

    Coming out of Saarland University is Vcc, the Vulkan Clang Compiler.

    Vcc provides an “honest attempt to bring the entire C/C++ language family to Vulkan” as an interesting new compiler.

    Vcc intends to support every legal use of these constructs per C/C++ language standards.

    Vcc leverages the Shady project as an IR and compiler for extending the SPIR-V intermediate representation.

    More details on the Vulkan Clang Compiler, which is still considered in its early stages of development, via this blog post and the new Vcc project site.

    It will be very interesting to see where Vcc ends up and what new avenues it opens for Vulkan and GPU computing.

    The original article contains 132 words, the summary contains 109 words. Saved 17%. I’m a bot and I’m open source!