[Python-Dev] Inplace operations for PyLong objects

Manciu, Catalin Gabriel catalin.gabriel.manciu at intel.com
Thu Aug 31 14:40:07 EDT 2017

Hi everyone,

While looking over the PyLong source code in Objects/longobject.c I came
across the fact that the PyLong object doesnt't include implementation for
basic inplace operations such as adding or multiplication:

    long_long,                  /*nb_int*/
    0,                          /*nb_reserved*/
    long_float,                 /*nb_float*/
    0,                          /* nb_inplace_add */
    0,                          /* nb_inplace_subtract */
    0,                          /* nb_inplace_multiply */
    0,                          /* nb_inplace_remainder */

While I understand that the immutable nature of this type of object justifies
this approach, I wanted to experiment and see how much performance an inplace
add would bring.
My inplace add will revert to calling the default long_add function when:
	- the refcount of the first operand indicates that it's being shared
	- that operand is one of the preallocated 'small ints'
which should mitigate the effects of not conforming to the PyLong immutability
It also allocates a new PyLong _only_ in case of a potential overflow.

The workload I used to evaluate this is a simple script that does a lot of
inplace adding:

	import time
	import sys

	def write_progress(prev_percentage, value, limit):
		percentage = (100 * value) // limit
		if percentage != prev_percentage:
			sys.stdout.write("%d%%\r" % (percentage))
		return percentage

	progress = -1
	the_value = 0
	the_increment = ((1 << 30) - 1)
	crt_iter = 0
	total_iters = 10 ** 9

	start = time.time()

	while crt_iter < total_iters:
		the_value += the_increment
		crt_iter += 1
		progress = write_progress(progress, crt_iter, total_iters)

	end = time.time()

	print ("\n%.3fs" % (end - start))
	print ("the_value: %d" % (the_value))

Running the baseline version outputs:
./python inplace.py
the_value: 1073741823000000000

Running the modified version outputs:
./python inplace.py
the_value: 1073741823000000000

In summary, I got a +13.47% improvement for the modified version.
The CPython revision I'm using is 7f066844a79ea201a28b9555baf4bceded90484f
from the master branch and I'm running on a I7 6700K CPU with Turbo-Boost
disabled (frequency is pinned at 4GHz).

Do you think that such an optimization would be a good approach ?

Thank you,

More information about the Python-Dev mailing list