biswapanda / numpile Goto Github PK

A tiny 1000 line LLVM-based numeric specializer for scientific Python code.

You really shouldn't use this for anything serious, it's just to demonstrate how you might build one of these things from scratch. There's a lot of untapped potential and low hanging fruit around selective embedded JIT specialization for array expression languages in the SciPython space.

Just install Anaconda and it will work out of box.

Or if you like suffering then install LLVM from your package manager and then have fun installing llvmpy and numpy from source.

$ pip install llvmpy
$ pip install numpy

from numpile import autojit

@autojit
def dot(a, b):
    c = 0
    n = a.shape[0]
    for i in range(n):
       c += a[i]*b[i]
    return c

a = np.array(range(1000,2000), dtype='int32')
b = np.array(range(3000,4000), dtype='int32')

print dot(a,b)

Released under the MIT License. Copyright (c) 2015, Stephen Diehl