[cfe-dev] libc++ Performance (compared to libstdc++)
Craig, Ben via cfe-dev
cfe-dev at lists.llvm.org
Tue Jul 5 09:40:16 PDT 2016
If you're looking for "fair" comparisons between the library portions of
libc++ and libstdc++, it may make more sense to use g++ as the compiler
instead. I'm pretty sure that libc++ works with g++, and I also believe
that the libstdc++ that ships with gcc 5.0+ no longer uses the
non-conforming COW strings. I would suggest using clang++ with a newer
libstdc++, but I believe that isn't currently supported due to some ABI
tag weirdness.
On 7/2/2016 5:03 AM, Dennis Luehring via cfe-dev wrote:
> 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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