CPU：Intel® Core™ i7-5930K @ 3.50GHz
Python： 2.7.6
代码：
from itertools import izip, starmap, imap import operator import numpy as np import time r = range(10000) # method 1 np.dot(r,r) # method 2 sum(starmap(operator.mul, izip(r,r))) # method 3 out = 0 for k in range(len(r)): out += r[k] * r[k] # method 4 sum(map(operator.mul,r,r)) # method 5 sum(imap(operator.mul,r,r)) # method 6 sum(i*j for i, j in zip(r, r))统计在不同向量维度：
10, 100, 1000, 2000, 3000, 4000, 5000, 8000, 10000各运行三次：
10 1. 0.000285 0.000188 0.000309 2. 0.000117 6.3e-05 9.4e-05 3. 9.9e-05 6.1e-05 9.2e-05 4. 8.6e-05 4.4e-05 7.6e-05 5. 5.7e-05 4e-05 6.99999999999e-05 6. 9.3e-05 6e-05 8.29999999999e-05 100 1. 0.000513 0.00052 0.000504 2. 0.000169 0.000162 0.000167 3. 0.000451 0.000311 0.000288 4. 0.000137 0.000144 0.000153 5. 0.000131 0.000138 0.000141 6. 0.000224 0.000271 0.000216 1000 1. 0.001683 0.001687 0.001679 2. 0.000664 0.00065 0.000661 3. 0.002238 0.002301 0.002582 4. 0.000821 0.00089 0.00088 5. 0.000707 0.000928 0.000822 6. 0.001958 0.001948 0.00193 2000 1. 0.003138 0.00306 0.003158 2. 0.001197 0.001089 0.001075 3. 0.005211 0.004113 0.004399 4. 0.001891 0.001826 0.001953 5. 0.001415 0.001456 0.00173 6. 0.003595 0.003884 0.004285 3000 1. 0.004468 0.004292 0.004507 2. 0.001842 0.001727 0.001637 3. 0.007802 0.007341 0.006858 4. 0.002548 0.002274 0.0022 5. 0.002374 0.002348 0.002335 6. 0.005697 0.005613 0.005669 4000 1. 0.005946 0.005987 0.005954 2. 0.002251 0.002102 0.002189 3. 0.009069 0.010478 0.009226 4. 0.003149 0.003699 0.003363 5. 0.003032 0.003536 0.003142 6. 0.012805 0.012598 0.012316 5000 1. 0.007411 0.00731 0.007234 2. 0.002744 0.002508 0.002576 3. 0.012194 0.01231 0.009216 4. 0.003953 0.003815 0.003936 5. 0.00354 0.002698 0.002948 6. 0.013849 0.012262 0.015122 8000 1. 0.010604 0.011742 0.011604 2. 0.004712 0.004703 0.005037 3. 0.020271 0.014874 0.020436 4. 0.007199 0.006417 0.007193 5. 0.006887 0.006889 0.006892 6. 0.021665 0.021659 0.021992 10000 1. 0.01461 0.013028 0.014307 2. 0.005814 0.005789 0.005875 3. 0.023581 0.025064 0.025116 4. 0.008041 0.008833 0.008868 5. 0.007898 0.008619 0.008925 6. 0.025248 0.02643 0.026212
取运行时间的均值，绘制成曲线图，可以看出，几种方法里，第2种方法的复杂度最小，随着向量维度的增加，时间消耗增加比较缓慢，而其他方法则相对较大。