title: Performance between C-contiguous and Fortran-contiguous array operations
body: <p>Below, I compared performance when dealing with sum operations between C-contiguous and Fortran-contiguous arrays (<a href="http://www.visitusers.org/index.php?title=C_vs_Fortran_memory_order" rel="noreferrer">C vs FORTRAN memory order</a>). I set <code>axis=0</code> to ensure numbers are added up column wise. I was surprised that Fortran-contiguous array is actually slower than its C counterpart. Isn't that Fortran-contiguous array has contiguous memory allocation in columns and hence is better at column-wise operation?</p>
  
  <pre><code>import numpy as np
  a = np.random.standard_normal((10000, 10000))
  c = np.array(a, order='C')
  f = np.array(a, order='F')
  </code></pre>
  
  <p>In Jupyter notebook, run</p>
  
  <pre><code>%timeit c.sum(axis=0)
  10 loops, best of 3: 84.6 ms per loop
  </code></pre>
  
  
  
  <pre><code>%timeit f.sum(axis=0)
  10 loops, best of 3: 137 ms per loop
  </code></pre>