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I am wondering why mpmath is so much slower than decimal when doing the same operation for the same precision settings.

from decimal import *
from mpmath import *
import timeit
from decimal import Decimal as dc
from mpmath import mpf
import sys

# Set the same precision 
getcontext().prec = 15
mp.dps = 15

# A random function which does multiplication using mpmath
def mpf_test():
    a = mpf('2202020202002020.21212')
    b = mpf('3202020202002020.21212')
    c = mpf(0)
    for _ in range(10000):
        c += (a*b) / (a*b)

# The same function which does the multiplication using decimal
def decimal_test():
    a = dc('2202020202002020.21212')
    b = dc('3202020202002020.21212')
    c = dc(0.0)
    for _ in range(10000):
        c += (a*b) / (a*b)


# Print results
print(F"Using Decimal: {timeit.timeit(stmt=decimal_test, number=100)}")
print(F"Using mpmath: {timeit.timeit(stmt=mpf_test, number=100)}")

# Check if gmpy2 is used in mpmath
if 'gmpy2' in sys.modules:
    print(F"You are using gmpy2")

Output:

Using Decimal: 0.3805640869977651
Using mpmath: 2.961118871004146
You are using gmpy2

The difference is around a factor of 8..

I am using Python3.8, my machine is a new T14s with AMD7 and 32 GB RAM (Dont know if it makes any difference.. )

Yash Deshpande
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1 Answers1

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mpmath is written in Python. decimal is written in C. C extensions have less interpreter overhead. That's about it.

Note that even if you have gmpy2 installed, that just means mpmath will use gmpy2 integers instead of regular Python ints under the hood. It won't automatically C-accelerate the whole mpmath implementation.

user2357112
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  • Thanks for the answer. I would like to add that I similar testing was done using gmpy2.mpfr -- (which Is C-accelerated) and the results were comparable to decimal. In fact for the same test as above, gmpy2.mpfr was slightly faster at 3.3 seconds. – Yash Deshpande Jun 17 '21 at 09:21