[cfe-dev] libc++ Performance (compared to libstdc++)

Sat Jul 2 03:03:16 PDT 2016

these benchmarks could be a good starting point for an 
permanten/commit-based libc++ performance regression
test like LLD got 
(http://lists.llvm.org/pipermail/llvm-dev/2016-January/094132.html)

Am 02.07.2016 um 02:55 schrieb Hal Finkel via cfe-dev:
> Hi everyone,
>
> I was chatting with Marshall offline last week, and I mentioned that several of my users had noted general performance regressions switching from libstdc++ to libc++. Marshall said that he's heard similar things, but has received few specific reports. He did recall looking at the problem which I believe is described here (http://aras-p.info/blog/2015/12/11/careful-with-that-stl-map-insert-eugene/), which is still a problem. I'll certainly admit that I'd not investigated most of these in detail (with the exception of a std::complex -ffast-math issue, http://reviews.llvm.org/D18639). We do have a few performance-related libc++ bugs open:
>
> https://llvm.org/bugs/show_bug.cgi?id=21192 - Reading from stdin is 1-2 orders of magnitude slower than using libstdc++ [I just tested this myself and updated the bug report].
> https://llvm.org/bugs/show_bug.cgi?id=19708 - std::find is significantly slower than libstdc++.
> https://llvm.org/bugs/show_bug.cgi?id=20837 - libc++'s std::sort is O(N^2) in the worst case (instead of O(N*ln(N))).
> https://llvm.org/bugs/show_bug.cgi?id=26886 - libc++'s std::stable_sort also has a worst-case complexity issue.
> https://llvm.org/bugs/show_bug.cgi?id=15456 - A faster implementation of std::function is possible
> https://llvm.org/bugs/show_bug.cgi?id=16747 and https://llvm.org/bugs/show_bug.cgi?id=21275 - Our unordered_multimap insert is much slower than libstdc++'s. In PR16747, Howard interestingly explains libc++ has this problem because of an additional (i.e. not-required-by-the-standard) guarantee that libc++ provides regarding member ordering.
>
> but very few are related to containers.
>
> Baptiste Wicht has a benchmark covering use of several common standard algorithms with vectors, lists and dqueues (https://github.com/wichtounet/articles/blob/master/src/vector_list/bench.cpp) which he used for his post http://baptiste-wicht.com/posts/2012/12/cpp-benchmark-vector-list-deque.html, and I've compiled this using LLVM/Clang/libc++ r271873 @ -O3, using both libc++ and libstdc++ 4.8.5, and run on an Intel Xeon E5-2699 v3 @ 2.30GHz running Linux 3.10.0. If you try this yourself, note that even on a fast machine the benchmark takes several hours to run.
>
> $ clang++ -std=c++11 -O3 -I../../include -I../../../boost_1_61_0 bench.cpp ../demangle.cpp ../graphs.cpp -o /tmp/b-gnu
> $ clang++ -std=c++11 -stdlib=libc++ -O3 -I../../include -I../../../boost_1_61_0 bench.cpp ../demangle.cpp ../graphs.cpp -o /tmp/b-llvm
>
> Of the 248 tests, libc++ was faster by at least 5% in 58 of the tests and libstdc++ was faster by at least 5% in 94 of the tests. libc++ was faster by at least 20% in 14 of the tests and libstdc++ was faster by at least 20% in 64 of the tests. The real problem, however, comes from the extremums. libc++ is never more than 65% faster than libstdc++:
>
> destruction___Trivial_128_	list	-0.65
> destruction___Trivial_4096_	vector	-0.40
> destruction___Trivial_1024_	list	-0.38
> destruction___Trivial_1024_	vector	-0.37
> random_remove___NonTrivialArray_32_	vector	-0.3
>
> but libc++ is sometimes over 10x slower than libstdc++:
>
> fill_back___NonTrivialStringMovable	list_inserter	9.96
> fill_back___NonTrivialStringMovable	vector_reserve	10.21
> fill_back___NonTrivialStringMovableNoExcept	vector_reserve	10.82
> fill_back___NonTrivialStringMovableNoExcept	vector_inserter	11.15
> fill_back___NonTrivialStringMovable	vector_inserter	11.93
>
> I've attached the full list.
>
> A second benchmark, http://beta.visl.sdu.dk/svn/visl/tools/benchmarks/src/set.cpp (https://tinodidriksen.com/2012/02/20/cpp-set-performance-2/), modified only to repeat each test 30 instead of 7 times, and compiled as before:
>
> uint32_t std::set erase: -0.37
> std::string std::set erase: -0.30
> std::string std::set insertion: -0.23
> std::string std::unordered_set erase: -0.16
> std::string std::unordered_set iterate: -0.15
> std::string std::set lookup: -0.15
> uint32_t std::set insertion: -0.13
> uint32_t std::unordered_set iterate: -0.072
> std::string std::set iterate: -0.062
> uint32_t std::set iterate: -0.054
> uint32_t std::set lookup: -0.015
> uint32_t std::unordered_set erase: 0.085
> std::string std::unordered_set insertion: 0.22
> std::string std::unordered_set lookup: 0.30
> uint32_t std::unordered_set insertion: 0.51
> uint32_t std::unordered_set lookup: 0.61
>
> In this benchmark, libc++ beats libstdc++ by more than 5% in 10 tests, and libstdc++ beats libc++ by more than 5% in 5 tests. Again, however, libc++'s downside is larger, being up to 61% slower (in the 'uint32_t std::unordered_set lookup' test) than libstdc++. libstdc++ loses only by 37% to libc++, at most, in the 'uint32_t std::set erase' test. Also, I can easily imagine that users are more-likely to notice a performance difference in lookup than in erase.
>
> To pick another benchmark, I compiled and ran the one from http://www.reedbeta.com/blog/2015/01/12/data-oriented-hash-table/ - and this must be good because the post ends with, "And remember, if Chandler Carruth and Mike Acton give you advice about data structures, listen to them. ;)". I modified the benchmark only by adding constexpr to min() and max() of XorshiftRNG to make it compile with libc++. This benchmarks many configurations and takes nearly an hour to run. I'll summarize the results I'll say that libc++ is almost always slower than libstdc++, and that as the element size and/or the number of elements increases it gets worse. Here are the relative timing differences; these are tests for unordered_map:
>
> Fill for 8-byte elements, 32-byte elements, 128-byte elements, 1K-byte elements, 4K-byte elements:
> 100000 -0.022 0.026 0.10 0.057 0.058
> 200000 -0.028 0.0041 0.12 0.083 0.057
> 300000 -0.022 -0.023 0.018 0.040 0.035
> 400000 -0.010 -0.0094 -0.077 0.048 0.049
> 500000 0.22 0.28 0.18 0.17 0.094
> 600000 -0.064 -0.081 -0.11 0.0033 0.020
> 700000 -0.059 -0.043 -0.089 -0.0047 0.027
> 800000 -0.037 -0.053 -0.072 0.0092 0.035
> 900000 0.36 0.30 0.20 0.15 0.099
> 1000000 0.31 0.23 0.17 0.13 0.098
>
> The first column is the number of elements; negative numbers mean libc++ is faster. For 1000000 4K elements, libstdc++ is faster by 9.8%. For 1000000 8-byte elements, libstdc++ is faster by nearly 32%.
>
> Pre-sized fill:
> 100000 0.024 0.020 0.12 0.091 0.042
> 200000 0.015 0.016 0.16 0.041 0.084
> 300000 0.00038 0.033 0.17 0.090 0.090
> 400000 0.070 0.041 0.069 0.084 0.094
> 500000 0.069 0.025 0.061 0.12 0.10
> 600000 -0.0096 0.023 0.016 0.074 0.072
> 700000 0.060 0.0013 0.036 0.094 0.085
> 800000 0.029 -0.0048 0.035 0.083 0.075
> 900000 -0.011 0.0025 -0.037 0.078 0.085
> 1000000 0.0022 0.019 0.011 0.084 0.081
>
> Time for 100K lookups:
> 100000 0.12 0.13 0.089 0.11 0.071
> 200000 0.13 0.12 0.10 0.11 0.072
> 300000 0.098 0.12 0.053 0.085 0.080
> 400000 0.18 0.11 0.088 0.059 0.030
> 500000 0.12 0.080 0.072 0.075 0.033
> 600000 0.095 0.10 0.076 0.063 0.017
> 700000 0.17 0.097 0.12 0.083 0.043
> 800000 0.16 0.13 0.11 0.092 0.050
> 900000 0.094 0.086 0.056 0.041 -0.0047
> 1000000 0.14 0.11 0.092 0.073 0.016
>
> Time for 100K failed lookups:
> 100000 0.15 0.15 0.11 0.087 0.077
> 200000 0.14 0.11 0.083 0.074 0.059
> 300000 0.10 0.091 0.090 0.12 0.097
> 400000 0.10 0.12 0.061 0.11 0.099
> 500000 0.19 0.20 0.12 0.12 0.12
> 600000 0.18 0.18 0.12 0.11 0.095
> 700000 0.082 0.096 0.068 0.079 0.070
> 800000 0.20 0.19 0.14 0.13 0.12
> 900000 0.20 0.17 0.10 0.11 0.097
> 1000000 0.25 0.22 0.17 0.14 0.13
>
> Time to remove half the elements:
> 100000 0.15 0.15 0.078 0.066 0.066
> 200000 0.12 0.12 0.039 0.055 0.060
> 300000 0.12 0.070 0.024 0.038 0.095
> 400000 0.16 0.16 0.15 0.13 0.13
> 500000 0.10 0.12 0.12 0.13 0.13
> 600000 0.077 0.015 0.036 0.026 0.049
> 700000 0.086 0.16 0.16 0.17 0.14
> 800000 0.076 0.044 0.051 0.043 0.064
> 900000 0.11 0.11 0.11 0.12 0.13
> 1000000 0.10 0.090 0.061 0.081 0.10
>
> Many of our users have code that is sensitive to the performance of standard containers and algorithms, and this preliminary benchmarking lends support to the anecdotes that libc++ is slower than libstdc++. Worryingly, the extremes of these differences are pretty large. Obviously application impact can't be judged by some benchmarks I happened to find on the internet, but this is something we, as a community, should look at more closely.
>
> Thanks again,
> Hal
>
>
>
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