Next Decade in Languages: User Code on the GPU

1. raymarcher-benchmarks

   1 1 0 10.0 WebAssembly

   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.

2. InfluxDB

   influxdata.com featured

   InfluxDB high-performance time series database. Collect, organize, and act on massive volumes of high-resolution data to power real-time intelligent systems.

   

3. accelerate-llvm

   2 2 164 2.7 Haskell

   LLVM backend for Accelerate

   

   I’m personally a big fan of http://www.acceleratehs.org / https://github.com/AccelerateHS/accelerate-llvm

4. accelerate

   3 10 915 7.2 Haskell

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

   

   I’m personally a big fan of http://www.acceleratehs.org / https://github.com/AccelerateHS/accelerate-llvm

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