I have this
numpy code to try and compute the euclidean distance between
b and EVERY row of
a. I can’t get the speed to faster than 3.5s. But the best Julia solution I found can do this in about 75ms. Which is like almost 50x faster!
I have to admit I have never used numba but have heard lots of good things about it. I will start looking into how to write this in numba, but given it’s a simple problem, I wonder if anyone can help give me some example code to work from? Do I just write a loop and Numba will
my numpy code
import numpy as np # generate a = np.random.rand(4000000, 128) b = np.random.rand(128) print(a.shape) print(b.shape) def lin_norm_ever(a, b): return np.linalg.norm(a - b, axis=1) import time t = time.time() res = lin_norm_ever(a, b) print(res.shape) elapsed = time.time() - t print(elapsed)