Related: https://NN-512.com is a compiler that generates C99 code for neural net inference. It takes as input a simple text description of a convolutional neural net inference graph. It produces as output a human-readable, stand-alone (no dependencies) C99 implementation of that graph. The generated C99 code uses AVX-512 vector instructions to perform inference.
The compiler generates and serves its own website with no dependencies.
For personal projects (including NN-512) I use Mercurial for version control, not git. But in any case I don't want the compiler (or the website it generates) to depend on git or any other version control software.
For those surprised at the dot product benchmark on 3.1 [0] where np.dot() is substantially faster when using floats over ints, the things is simply that numpy can use BLAS libraries for floats, but not for ints (because BLAS libs don't implement integer data types).
