ruby/benchmark/array_sort_int.yml

prelude: |
  ary2 = 2.times.to_a.shuffle
  ary10 = 10.times.to_a.shuffle
  ary100 = 100.times.to_a.shuffle
  ary1000 = 1000.times.to_a.shuffle
  ary10000 = 10000.times.to_a.shuffle

benchmark:
  ary2.sort: ary2.sort
  ary10.sort: ary10.sort
  ary100.sort: ary100.sort
  ary1000.sort: ary1000.sort
  ary10000.sort: ary10000.sort

loop_count: 10000
Introduce BOP_CMP for optimized comparison Prior to this commit the `OPTIMIZED_CMP` macro relied on a method lookup to determine whether `<=>` was overridden. The result of the lookup was cached, but only for the duration of the specific method that initialized the cmp_opt_data cache structure. With this method lookup, `[x,y].max` is slower than doing `x > y ? x : y` even though there's an optimized instruction for "new array max". (John noticed somebody a proposed micro-optimization based on this fact in https://github.com/mastodon/mastodon/pull/19903.) ```rb a, b = 1, 2 Benchmark.ips do \|bm\| bm.report('conditional') { a > b ? a : b } bm.report('method') { [a, b].max } bm.compare! end ``` Before: ``` Comparison: conditional: 22603733.2 i/s method: 19820412.7 i/s - 1.14x (± 0.00) slower ``` This commit replaces the method lookup with a new CMP basic op, which gives the examples above equivalent performance. After: ``` Comparison: method: 24022466.5 i/s conditional: 23851094.2 i/s - same-ish: difference falls within error ``` Relevant benchmarks show an improvement to Array#max and Array#min when not using the optimized newarray_max instruction as well. They are noticeably faster for small arrays with the relevant types, and the same or maybe a touch faster on larger arrays. ``` $ make benchmark COMPARE_RUBY=<master@5958c305> ITEM=array_min $ make benchmark COMPARE_RUBY=<master@5958c305> ITEM=array_max ``` The benchmarks added in this commit also look generally improved. Co-authored-by: John Hawthorn <jhawthorn@github.com> 2022-11-23 05:16:11 +03:00			`prelude: \|`
			`ary2 = 2.times.to_a.shuffle`
			`ary10 = 10.times.to_a.shuffle`
			`ary100 = 100.times.to_a.shuffle`
			`ary1000 = 1000.times.to_a.shuffle`
			`ary10000 = 10000.times.to_a.shuffle`

			`benchmark:`
			`ary2.sort: ary2.sort`
			`ary10.sort: ary10.sort`
			`ary100.sort: ary100.sort`
			`ary1000.sort: ary1000.sort`
			`ary10000.sort: ary10000.sort`

			`loop_count: 10000`