In [42]:

    

%autosave 2
from multiprocessing import Pool, cpu_count
import numpy as np
from functools import partial

n_threads = cpu_count()


    

    















    




Autosaving every 2 seconds

In [24]:

    

n=1000001
def f(n=1000001):
    a = np.random.normal(scale=1, size=n)
    return np.mean(a)


    

In [25]:

    

%%timeit
for _ in range(n_threads):
    f()


    

    




422 ms ± 410 µs per loop (mean ± std. dev. of 7 runs, 1 loop each)

In [28]:

    

%%timeit
with Pool(processes=n_threads) as p:
    a = p.map(f, [1000001]*n_threads)


    

    




128 ms ± 165 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)

In [38]:

    

def sphere_volume(n, rndstate=None):
    if rndstate is None:
        a = np.random.uniform(-1, 1, size=(n, 3))
    else:
        rndstate.uniform(-1, 1, size=(n, 3))
    a_bool = np.sum(np.square(a), axis=1) < 1
    k = np.sum(a_bool)
    return k

n = int(1e7)
%timeit print((sphere_volume(n) / n * 8) / (4/3*np.pi))


    

    




0.999738395877
1.00037132326
1.00038602917
0.999736677004
0.999971398714
0.999604896711
1.00021108606
1.00010317901
950 ms ± 44.1 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)

In [37]:

    

%%timeit
with Pool(processes=n_threads) as p:
    v = p.map(sphere_volume, [n//n_threads]*n_threads)
print(sum(v) / n * 8 / (4/3*np.pi))


    

    




0.999906081525
0.999906081525
0.999906081525
0.999906081525
0.999906081525
0.999906081525
0.999906081525
0.999906081525
290 ms ± 49.9 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)

In [48]:

    

args = [(n//n_threads, np.random.RandomState())
        for _ in range(n_threads)]
with Pool(processes=n_threads) as p:
    v = p.starmap(
        sphere_volume,
        args
    )
print(sum(v) / n * 8 / (4/3*np.pi))


    

    




---------------------------------------------------------------------------
RemoteTraceback                           Traceback (most recent call last)
RemoteTraceback: 
"""
Traceback (most recent call last):
  File "/opt/conda/lib/python3.6/multiprocessing/pool.py", line 119, in worker
    result = (True, func(*args, **kwds))
  File "/opt/conda/lib/python3.6/multiprocessing/pool.py", line 47, in starmapstar
    return list(itertools.starmap(args[0], args[1]))
  File "<ipython-input-38-9fdeef156ad8>", line 6, in sphere_volume
    a_bool = np.sum(np.square(a), axis=1) < 1
UnboundLocalError: local variable 'a' referenced before assignment
"""

The above exception was the direct cause of the following exception:

UnboundLocalError                         Traceback (most recent call last)
<ipython-input-48-87a3c8f3efae> in <module>()
      4     v = p.starmap(
      5         sphere_volume,
----> 6         args
      7     )
      8 print(sum(v) / n * 8 / (4/3*np.pi))

/opt/conda/lib/python3.6/multiprocessing/pool.py in starmap(self, func, iterable, chunksize)
    272         `func` and (a, b) becomes func(a, b).
    273         '''
--> 274         return self._map_async(func, iterable, starmapstar, chunksize).get()
    275 
    276     def starmap_async(self, func, iterable, chunksize=None, callback=None,

/opt/conda/lib/python3.6/multiprocessing/pool.py in get(self, timeout)
    642             return self._value
    643         else:
--> 644             raise self._value
    645 
    646     def _set(self, i, obj):

UnboundLocalError: local variable 'a' referenced before assignment

In [ ]: