On 8/31/2017 2:40 PM, Manciu, Catalin Gabriel wrote:
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 or - that operand is one of the preallocated 'small ints' which should mitigate the effects of not conforming to the PyLong immutability specification. 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)) sys.stdout.flush() 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 100% 356.633s the_value: 1073741823000000000 Running the modified version outputs: ./python inplace.py 100% 308.606s 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 ?
On my machine, the more realistic code, with an implicit C loop, the_value = sum(the_increment for i in range(total_iters)) gives the same value twice as fast as your explicit Python loop. (I cut total_iters down to 10**7). You might check whether sum uses an in-place accumulator for ints. -- Terry Jan Reedy _______________________________________________ Python-Dev mailing list Python-Dev@python.org https://mail.python.org/mailman/listinfo/python-dev Unsubscribe: https://mail.python.org/mailman/options/python-dev/archive%40mail-archive.com
