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The two following single-threading and multi-threading scripts are taking the same time when I give as input a big number like 555550000

single thread

import threading, time a=[] def print_factors(x): for i in range(1, x + 1): if x % i == 0: a.append(i) n=int(input("Please enter a large number")) print ("Starting time is %s" % ( time.ctime(time.time()) )) print("The factors of",n,"are:") thread = threading.Thread(target=print_factors,args=(n,)) thread.start() thread.join() print("Finishing time is %s" % (time.ctime(time.time()))) print(a)

multi thread

import threading, time a=[] def print_factors1(x): for i in range(1, int(x/2)): if x % i == 0: a.append(i) def print_factors2(x): for i in range(int(x/2), x+1): if x % i == 0: a.append(i) n=int(input("Please enter a large number")) print ("Starting time is %s" % ( time.ctime(time.time()) )) thread1 = threading.Thread(target=print_factors1,args=(n,)) thread2 = threading.Thread(target=print_factors2,args=(n,)) print("The factors of",n,"are:") thread1.start() thread2.start() thread2.join() print("Finishing time is %s" % (time.ctime(time.time()))) print(a)

I am trying to understand the difference between single-threading and multi-threading in terms of time taken to got the results.
I'm measuring similar timings for both types and I cannot figuring out the reasons.

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  • 2
    Due to the GIL, you will not get an performance improvement on CPU-bound tasks. Commented Jun 2, 2020 at 15:10
  • @JanChristophTerasa any ideas how to fix it? Commented Jun 2, 2020 at 15:32
  • To make it clear, the problem is CPython's GIL, not multithreading in general. If you are not limited to Python, you can easily write a multithreaded program in C++, golang or Rust. Commented Jun 2, 2020 at 18:04

1 Answer 1

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Your problem is GIL, the Global Interpreter Lock.

The Python Global Interpreter Lock or GIL, in simple words, is a mutex (or a lock) that allows only one thread to hold the control of the Python interpreter.

You can found detailed informations about GIL here (just a fast search on Google and you can find a lot more sources):

You need to change your implementation to use processes instead of threads.
I changed your script as follows:

from multiprocessing import Pool import time def print_factors1(x): a=[] for i in range(1, int(x/2)): if x % i == 0: a.append(i) return a def print_factors2(x): a=[] for i in range(int(x/2), x+1): if x % i == 0: a.append(i) return a if __name__ == '__main__': n=int(input("Please enter a large number")) pool = Pool(processes=2) print ("Starting time is %s" % ( time.ctime(time.time()) )) process1 = pool.apply_async(print_factors1,[n]) process2 = pool.apply_async(print_factors2,[n]) pool.close() pool.join() print("Finishing time is %s" % (time.ctime(time.time()))) print("The factors of",n,"are:") print(process1.get()) print(process2.get())

Take into account that threads share the memory, processes don't.

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2 Comments

The thing is the assignment asks to use an application to show the difference between single and multithreading time, should I contact the proffesor and tell him that's not possible due to the GLI?
You are welcome. Your code shows the difference between single and multi thread. If you need performance boost on CPU-bound tasks, you need to switch to multiprocess implementation. Take a look to the GIL and you'll have a lot of things to explain to your prof.

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