is a new SIMD library focused on providing portable SIMD acceleration of SoA (Structure of Arrays) algorithms, using consistent-length SIMD vectors for lockstep iteration and computation. Extensive research and work has gone into minimizing wasted CPU cycles and making the most out of what your CPU can do.
I've been working on Thermite for a little over a month now, and with the AVX2 backend and vectorized math library almost fully implemented, I think now is a good time to announce the crate and ask for feedback. Pre-AVX2/WASM/ARM backends are a work in progress.
The latest documentation is at https://raygon-renderer.github.io/thermite/
What would you like to see in an ideal SIMD framework? What can be done better in Thermite? What would be required to use Thermite in your number-crunching applications?