NAME
Bencher::Scenario::ArraySet::symdiff - Benchmark symmetric difference operation
VERSION
This document describes version 0.002 of Bencher::Scenario::ArraySet::symdiff (from Perl distribution Bencher-Scenarios-ArraySet), released on 2016-09-16.
SYNOPSIS
To run benchmark with default option:
% bencher -m ArraySet::symdiffTo run module startup overhead benchmark:
% bencher --module-startup -m ArraySet::symdiffFor more options (dump scenario, list/include/exclude/add participants, list/include/exclude/add datasets, etc), see bencher or run bencher --help.
BENCHMARKED MODULES
Version numbers shown below are the versions used when running the sample benchmark.
Array::Set 0.05
Set::Object 1.35
Set::Scalar 1.29
BENCHMARK PARTICIPANTS
Array::Set::set_symdiff (perl_code)
Function call template:
Array::Set::set_symdiff(<set1>, <set2>)Set::Object::symmetric_difference (perl_code)
Code template:
my $set1 = Set::Object->new; $set1->insert(@{<set1>}); my $set2 = Set::Object->new; $set2->insert(@{<set2>}); my $res = $set1->symmetric_difference($set2);Set::Scalar::symmetric_difference (perl_code)
Code template:
my $set1 = Set::Scalar->new; $set1->insert(@{<set1>}); my $set2 = Set::Scalar->new; $set2->insert(@{<set2>}); my $res = $set1->symmetric_difference($set2);
BENCHMARK DATASETS
1_1
10_1
10_5
10_10
100_1
100_10
100_100
1000_1
1000_10
1000_100
1000_1000
SAMPLE BENCHMARK RESULTS
Run on: perl: v5.24.0, CPU: Intel(R) Core(TM) M-5Y71 CPU @ 1.20GHz (2 cores), OS: GNU/Linux LinuxMint version 17.3, OS kernel: Linux version 3.19.0-32-generic.
Benchmark with bencher -m ArraySet::symdiff --include-path archive/Array-Set-0.02/lib --include-path archive/Array-Set-0.05/lib --multimodver Array::Set:
#table1#
{dataset=>"1000_1"}
+-----------------------------------+--------+-----------+-----------+------------+---------+---------+
| participant | modver | rate (/s) | time (ms) | vs_slowest | errors | samples |
+-----------------------------------+--------+-----------+-----------+------------+---------+---------+
| Array::Set::set_symdiff | 0.02 | 320 | 3.13 | 1 | 2.4e-06 | 21 |
| Set::Scalar::symmetric_difference | | 426 | 2.35 | 1.33 | 1.8e-06 | 20 |
| Set::Object::symmetric_difference | | 1070 | 0.934 | 3.35 | 6.9e-07 | 20 |
| Array::Set::set_symdiff | 0.05 | 1850 | 0.541 | 5.77 | 4.8e-07 | 20 |
+-----------------------------------+--------+-----------+-----------+------------+---------+---------+
#table2#
{dataset=>"1000_10"}
+-----------------------------------+--------+-----------+-----------+------------+---------+---------+
| participant | modver | rate (/s) | time (ms) | vs_slowest | errors | samples |
+-----------------------------------+--------+-----------+-----------+------------+---------+---------+
| Array::Set::set_symdiff | 0.02 | 315 | 3.18 | 1 | 2e-06 | 20 |
| Set::Scalar::symmetric_difference | | 420 | 2.4 | 1.3 | 2.5e-06 | 20 |
| Set::Object::symmetric_difference | | 1000 | 1 | 3.2 | 6.3e-06 | 21 |
| Array::Set::set_symdiff | 0.05 | 1800 | 0.55 | 5.8 | 6.4e-07 | 20 |
+-----------------------------------+--------+-----------+-----------+------------+---------+---------+
#table3#
{dataset=>"1000_100"}
+-----------------------------------+--------+-----------+-----------+------------+---------+---------+
| participant | modver | rate (/s) | time (ms) | vs_slowest | errors | samples |
+-----------------------------------+--------+-----------+-----------+------------+---------+---------+
| Array::Set::set_symdiff | 0.02 | 284 | 3.52 | 1 | 6.9e-07 | 20 |
| Set::Scalar::symmetric_difference | | 380 | 2.6 | 1.3 | 3.1e-06 | 20 |
| Set::Object::symmetric_difference | | 970 | 1.03 | 3.42 | 4.3e-07 | 20 |
| Array::Set::set_symdiff | 0.05 | 1690 | 0.592 | 5.95 | 4.8e-07 | 20 |
+-----------------------------------+--------+-----------+-----------+------------+---------+---------+
#table4#
{dataset=>"1000_1000"}
+-----------------------------------+--------+-----------+-----------+------------+---------+---------+
| participant | modver | rate (/s) | time (ms) | vs_slowest | errors | samples |
+-----------------------------------+--------+-----------+-----------+------------+---------+---------+
| Array::Set::set_symdiff | 0.02 | 155 | 6.43 | 1 | 2e-06 | 20 |
| Set::Scalar::symmetric_difference | | 250 | 4 | 1.6 | 4.9e-06 | 20 |
| Set::Object::symmetric_difference | | 824 | 1.21 | 5.3 | 5.9e-07 | 20 |
| Array::Set::set_symdiff | 0.05 | 1370 | 0.728 | 8.84 | 2.5e-07 | 22 |
+-----------------------------------+--------+-----------+-----------+------------+---------+---------+
#table5#
{dataset=>"100_1"}
+-----------------------------------+--------+-----------+-----------+------------+---------+---------+
| participant | modver | rate (/s) | time (μs) | vs_slowest | errors | samples |
+-----------------------------------+--------+-----------+-----------+------------+---------+---------+
| Array::Set::set_symdiff | 0.02 | 3000 | 330 | 1 | 4.3e-07 | 20 |
| Set::Scalar::symmetric_difference | | 3680 | 272 | 1.21 | 2.1e-07 | 20 |
| Set::Object::symmetric_difference | | 10000 | 100 | 3.3 | 1.3e-07 | 20 |
| Array::Set::set_symdiff | 0.05 | 21600 | 46.2 | 7.11 | 1.3e-08 | 20 |
+-----------------------------------+--------+-----------+-----------+------------+---------+---------+
#table6#
{dataset=>"100_10"}
+-----------------------------------+--------+-----------+-----------+------------+---------+---------+
| participant | modver | rate (/s) | time (μs) | vs_slowest | errors | samples |
+-----------------------------------+--------+-----------+-----------+------------+---------+---------+
| Array::Set::set_symdiff | 0.02 | 2750 | 364 | 1 | 1.9e-07 | 24 |
| Set::Scalar::symmetric_difference | | 3380 | 296 | 1.23 | 2.5e-07 | 22 |
| Set::Object::symmetric_difference | | 9100 | 110 | 3.3 | 2.2e-07 | 29 |
| Array::Set::set_symdiff | 0.05 | 20200 | 49.4 | 7.37 | 3.7e-08 | 23 |
+-----------------------------------+--------+-----------+-----------+------------+---------+---------+
#table7#
{dataset=>"100_100"}
+-----------------------------------+--------+-----------+-----------+------------+---------+---------+
| participant | modver | rate (/s) | time (μs) | vs_slowest | errors | samples |
+-----------------------------------+--------+-----------+-----------+------------+---------+---------+
| Array::Set::set_symdiff | 0.02 | 1540 | 650 | 1 | 2.5e-07 | 22 |
| Set::Scalar::symmetric_difference | | 2360 | 424 | 1.53 | 1.9e-07 | 24 |
| Set::Object::symmetric_difference | | 8200 | 120 | 5.3 | 2.1e-07 | 21 |
| Array::Set::set_symdiff | 0.05 | 16000 | 62 | 11 | 9.9e-08 | 23 |
+-----------------------------------+--------+-----------+-----------+------------+---------+---------+
#table8#
{dataset=>"10_1"}
+-----------------------------------+--------+-----------+-----------+------------+---------+---------+
| participant | modver | rate (/s) | time (μs) | vs_slowest | errors | samples |
+-----------------------------------+--------+-----------+-----------+------------+---------+---------+
| Set::Scalar::symmetric_difference | | 16833.4 | 59.4056 | 1 | 5.8e-11 | 25 |
| Array::Set::set_symdiff | 0.02 | 25000 | 40 | 1.5 | 4.4e-08 | 30 |
| Set::Object::symmetric_difference | | 60000 | 17 | 3.5 | 2.7e-08 | 20 |
| Array::Set::set_symdiff | 0.05 | 150000 | 6.8 | 8.7 | 9.3e-09 | 23 |
+-----------------------------------+--------+-----------+-----------+------------+---------+---------+
#table9#
{dataset=>"10_10"}
+-----------------------------------+--------+-----------+-----------+------------+---------+---------+
| participant | modver | rate (/s) | time (μs) | vs_slowest | errors | samples |
+-----------------------------------+--------+-----------+-----------+------------+---------+---------+
| Set::Scalar::symmetric_difference | | 14000 | 73 | 1 | 9.7e-08 | 24 |
| Array::Set::set_symdiff | 0.02 | 14200 | 70.6 | 1.03 | 2.7e-08 | 20 |
| Set::Object::symmetric_difference | | 54600 | 18.32 | 3.964 | 3.1e-10 | 25 |
| Array::Set::set_symdiff | 0.05 | 125915 | 7.94185 | 9.14294 | 0 | 20 |
+-----------------------------------+--------+-----------+-----------+------------+---------+---------+
#table10#
{dataset=>"10_5"}
+-----------------------------------+--------+-----------+-----------+------------+---------+---------+
| participant | modver | rate (/s) | time (μs) | vs_slowest | errors | samples |
+-----------------------------------+--------+-----------+-----------+------------+---------+---------+
| Set::Scalar::symmetric_difference | | 15000 | 66 | 1 | 1e-07 | 33 |
| Array::Set::set_symdiff | 0.02 | 18358 | 54.4723 | 1.21645 | 4.3e-11 | 20 |
| Set::Object::symmetric_difference | | 56600 | 17.7 | 3.75 | 6.7e-09 | 20 |
| Array::Set::set_symdiff | 0.05 | 136000 | 7.36 | 9 | 2.6e-09 | 32 |
+-----------------------------------+--------+-----------+-----------+------------+---------+---------+
#table11#
{dataset=>"1_1"}
+-----------------------------------+--------+-----------+-----------+------------+---------+---------+
| participant | modver | rate (/s) | time (μs) | vs_slowest | errors | samples |
+-----------------------------------+--------+-----------+-----------+------------+---------+---------+
| Set::Scalar::symmetric_difference | | 27100 | 36.8 | 1 | 1.3e-08 | 20 |
| Array::Set::set_symdiff | 0.02 | 91000 | 11 | 3.3 | 1.1e-08 | 27 |
| Set::Object::symmetric_difference | | 120000 | 8.3 | 4.5 | 1.3e-08 | 20 |
| Array::Set::set_symdiff | 0.05 | 350000 | 2.8 | 13 | 3.3e-09 | 20 |
+-----------------------------------+--------+-----------+-----------+------------+---------+---------+Benchmark module startup overhead (bencher -m ArraySet::symdiff --module-startup):
#table12#
+---------------------+-----------+------------------------+------------+---------+---------+
| participant | time (ms) | mod_overhead_time (ms) | vs_slowest | errors | samples |
+---------------------+-----------+------------------------+------------+---------+---------+
| Set::Object | 17 | 12.5 | 1 | 9.3e-05 | 20 |
| Set::Scalar | 15 | 10.5 | 1.1 | 2.8e-05 | 21 |
| Array::Set | 8 | 3.5 | 2.1 | 3.2e-05 | 20 |
| perl -e1 (baseline) | 4.5 | 0 | 3.7 | 8.5e-06 | 20 |
+---------------------+-----------+------------------------+------------+---------+---------+DESCRIPTION
Packaging a benchmark script as a Bencher scenario makes it convenient to include/exclude/add participants/datasets (either via CLI or Perl code), send the result to a central repository, among others . See Bencher and bencher (CLI) for more details.
HOMEPAGE
Please visit the project's homepage at https://metacpan.org/release/Bencher-Scenarios-ArraySet.
SOURCE
Source repository is at https://github.com/perlancar/perl-Bencher-Scenarios-ArraySet.
BUGS
Please report any bugs or feature requests on the bugtracker website https://rt.cpan.org/Public/Dist/Display.html?Name=Bencher-Scenarios-ArraySet
When submitting a bug or request, please include a test-file or a patch to an existing test-file that illustrates the bug or desired feature.
SEE ALSO
AUTHOR
perlancar <perlancar@cpan.org>
COPYRIGHT AND LICENSE
This software is copyright (c) 2016 by perlancar@cpan.org.
This is free software; you can redistribute it and/or modify it under the same terms as the Perl 5 programming language system itself.