what_exactly_does_'vectorisation'_mean?1

d1a18961-ac19-436d-a487-290f100db8dc.py

# import numba
from numba import jit
# define our function to profile our compiled code
def find_instr(func, keyword, sig=0, limit=5):
    count = 0
    # iterate over each of the assembly instructions and check if they match our chosen string
    for l in func.inspect_asm(func.signatures[sig]).split('\n'):
        if keyword in l or keyword == '':
            count += 1
            print(l)
            if count >= limit:
                break
    if count == 0:
        print('No instructions found')
# apply numba's just-in-time compilation
@jit(nopython=True, fastmath=True)
def arr_sum(arr):
    total = 0
    for i in range(arr.shape[0]):
        total += arr[i]
    return total
# define array
arr = np.arange(0, 1_000_000)
# run function (so it compiles at least once)
arr_sum(arr)
# inspect instruction set for additions
find_instr(arr_sum, 'add', limit=5)