Next Decade in Languages: User Code on the GPU

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  • raymarcher-benchmarks

    Simple benchmark of serial Rust vs. Vulkan SPIR-V vs. ISPC

    Something along similar lines but with a much lower barrier to entry that might be worth trying first is doing something similar to ISPC: essentially forcing vectorization of the whole program. This is the exact same thing that running on the GPU does, but on the CPU, so it doesn't require generating a whole new target language and inserting all the Vulcan/CUDA set up code. It's not as fast as the GPU, but it's a lot faster than regular CPU loops: in a benchmark from a couple years ago, I found that single-threaded ISPC beat single-threaded non-ISPC by a factor of about 6.5x, and multithreaded ISPC was only about 3x slower than GPU. For some reason multithreaded ISPC is only slightly more than 2x faster than normal multithreaded, but still a significant improvement.

  • accelerate-llvm

    LLVM backend for Accelerate

    I’m personally a big fan of /

  • Scout APM

    Less time debugging, more time building. Scout APM allows you to find and fix performance issues with no hassle. Now with error monitoring and external services monitoring, Scout is a developer's best friend when it comes to application development.

  • accelerate

    Embedded language for high-performance array computations (by AccelerateHS)

    I’m personally a big fan of /

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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