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From Chris Olivier <cjolivie...@apache.org>
Subject Re: [Discussion] Remove bundled llvm OpenMP
Date Thu, 22 Nov 2018 15:50:02 GMT
Do you not work on CI mostly? My apologies for thinking that was some sort
of team effort between you and a few others that were passionate about CI
keeping the CI system running smoothly.

You have source code, you have the line the assertion is on. If you can’t
describe what’s going wrong that causes the assertion, then I don’t really
have anything more to add to this conversation beyond what’s below:

The whole “mixing omp libraries” is something that occurs in production
every day and certainly in everything that uses mkl.  It may occasionally
cause problems for some edge cases when there is super-complex linking
strategies and dynamic loading.  But this is not one of those edge cases.
Mostly blaming this is a red herring for other thread-related problems and
people switch omp library and the timing of their code changes and they
stop seeing the problem. I’ve spent my entire career doing heavily
multiphreaded c++ development and i’ve seen that a million times.  is the
suggestion that libiomp be removed from mkl? have you spoken with intel?
have you consulted Intel at all?

and what you are seeing isn’t some “hard to debug random crash”. you’re
seeing an assertion which is probably related to omp trying to create a
thread pool after a fork and something was done in the mxnet code to make
that sketchy to do. I’d suggest filing an issue with the llvm openmp just
like you’d file with any other not-well-understood behavior in mxnet.

The lack of root-causing the problem and knee-jerk solution here makes me
uncomfortable.

if you want to see performance differences there’s an environment variable
you can set in the mxnet omp tuning code that will print overhead and
execution times for the current omp library.







On Thu, Nov 22, 2018 at 7:12 AM Anton Chernov <mechernov@gmail.com> wrote:

> Hi Chris,
>
> Thank you for your answer. If you have noticed the initial email comes from
> me, Anton Chernov (@lebeg on Github) and thus the proposal is not from any
> 'Ci' team that you've mentioned, but from me personally.
>
> You are writing:
>
> > someone is doing something unhealthy when they fork ...
>
> I'm missing any context to understand what you mean.
>
> > we get a lot of performance gain from OMP ...
>
> There is no data that would prove this statement and therefore it is a
> random guess.
>
> > in many months, no investigation has occurred as to WHY the assertion is
> failing.
>
> The investigation has concluded that this is happening due to undefined
> behaviour which is, in my opinion, a suffient answer that does not require
> to go any deeper.
>
> > the pr is vetoed until such a time that the actual root cause of the
> problem is known.
>
> And considering the statements above there is no valid reason to veto the
> PR.
>
>
> Best
> Anton
>
> чт, 22 нояб. 2018 г. в 15:38, Chris Olivier <cjolivier01@gmail.com>:
>
> > 3x less overhead*
> >
> > On Thu, Nov 22, 2018 at 6:25 AM Chris Olivier <cjolivier01@gmail.com>
> > wrote:
> >
> > > someone is doing something unhealthy when they fork, which is causing
> an
> > > assertion in the openmp library. the same assertion that would fire in
> > mkl,
> > > which is linked to libiomp5 (exact same omp library). this is new
> > behavior
> > > and most likely due to an error or suboptimal approach in the forking
> > logic
> > > in mxnet.
> > >
> > > in order to circumvent the assert, the Ci team is proposing to remove
> the
> > > library completely which is equivalent to cutting off your leg to make
> > the
> > > pain from stubbing your toe go away.
> > >
> > > we get a lot of performance gain from OMP. is has about a 1/3 less
> > > overhead for entering omp regions and also supports omp regions after a
> > > fork, which libgomp does not.
> > >
> > > in many months, no investigation has occurred as to WHY the assertion
> is
> > > failing.
> > >
> > > the pr is vetoed until such a time that the actual root cause of the
> > > problem is known.
> > >
> > >
> > > thanks,
> > >
> > > -Chris.
> > >
> > >
> > >
> > >
> > > On Thu, Nov 22, 2018 at 4:36 AM Anton Chernov <mechernov@gmail.com>
> > wrote:
> > >
> > >> Dear MXNet community,
> > >>
> > >> I would like to drive attention to an important issue that is present
> in
> > >> the MXNet CMake build: usage of bundled llvm OpenMP library.
> > >>
> > >> I have opened a PR to remove it:
> > >> https://github.com/apache/incubator-mxnet/pull/12160
> > >>
> > >> The issue was closed, but I am strong in my oppinion that it's the
> right
> > >> thing to do.
> > >>
> > >> *Background*
> > >> If you want to use OpenMP pragmas in your code for parallelization you
> > >> would supply a special flag to the compiler:
> > >>
> > >> - Clang / -fopenmp
> > >> https://openmp.llvm.org/
> > >>
> > >> - GCC / -fopenmp
> > >> https://gcc.gnu.org/onlinedocs/libgomp/Enabling-OpenMP.html
> > >>
> > >> - Intel / [Q]openmp
> > >>
> > >>
> >
> https://software.intel.com/en-us/node/522689#6E24682E-F411-4AE3-A04D-ECD81C7008D1
> > >>
> > >> - Visual Studio: /openmp (Enable OpenMP 2.0 Support)
> > >> https://msdn.microsoft.com/en-us/library/tt15eb9t.aspx
> > >>
> > >> Each of the compilers would enable the '#pragma omp' directive during
> > >> C/C++
> > >> compilation and arrange for automatic linking of the OpenMP runtime
> > >> library
> > >> supplied by each complier separately.
> > >>
> > >> Thus, to use the advantages of an OpenMP implementation one has to
> > compile
> > >> the code with the corresponding compiler.
> > >>
> > >> Currently, in MXNet CMake build scripts a bundled version of llvm
> OpenMP
> > >> is
> > >> used ([1] and [2]) to replace the OpenMP library supplied by the
> > compiler.
> > >>
> > >> I will quote here the README from the MKL-DNN (Intel(R) Math Kernel
> > >> Library
> > >> for Deep Neural Networks):
> > >>
> > >> "Intel MKL-DNN uses OpenMP* for parallelism and requires an OpenMP
> > runtime
> > >> library to work. As different OpenMP runtimes may not be binary
> > compatible
> > >> it's important to ensure that only one OpenMP runtime is used
> throughout
> > >> the application. Having more than one OpenMP runtime initialized may
> > lead
> > >> to undefined behavior resulting in incorrect results or crashes." [3]
> > >>
> > >> And:
> > >>
> > >> "Using GNU compiler with -fopenmp and -liomp5 options will link the
> > >> application with both Intel and GNU OpenMP runtime libraries. This
> will
> > >> lead to undefined behavior of the application." [4]
> > >>
> > >> As can be seen from ldd for MXNet:
> > >>
> > >> $ ldd build/tests/mxnet_unit_tests | grep omp
> > >>     libomp.so =>
> /.../mxnet/build/3rdparty/openmp/runtime/src/libomp.so
> > >> (0x00007f697bc55000)
> > >>     libgomp.so.1 => /usr/lib/x86_64-linux-gnu/libgomp.so.1
> > >> (0x00007f69660cd000)
> > >>
> > >> *Performance*
> > >>
> > >> The only performance data related to OpenMP in MXNet I was able to
> find
> > is
> > >> here:
> > >>
> > >>
> >
> https://github.com/apache/incubator-mxnet/issues/9744#issuecomment-367711172
> > >>
> > >> Which in my understanding is testing imact of different environment
> > >> variables for the same setup (using same bundled OpenMP library).
> > >>
> > >> The libraries may differ in implementation and the Thread Affinity
> > >> Interface [5] may have significant impact on performance.
> > >>
> > >> All compliers support it:
> > >>
> > >> - Clang / KMP_AFFINITY
> > >>
> > >>
> >
> https://github.com/clang-ykt/openmp/blob/master/runtime/src/kmp_affinity.cpp
> > >>
> > >> - GCC / GOMP_CPU_AFFINITY
> > >>
> > >>
> >
> https://gcc.gnu.org/onlinedocs/gcc-4.7.1/libgomp/GOMP_005fCPU_005fAFFINITY.html
> > >>
> > >> - Intel / KMP_AFFINITY
> > >>
> > >>
> >
> https://software.intel.com/en-us/node/522689#6E24682E-F411-4AE3-A04D-ECD81C7008D1
> > >>
> > >> - Visual Studio / SetThreadAffinityMask
> > >>
> > >>
> >
> https://docs.microsoft.com/en-us/windows/desktop/api/winbase/nf-winbase-setthreadaffinitymask
> > >>
> > >> *Issues*
> > >>
> > >> Failed OpenMP assertion when loading MXNet compiled with DEBUG=1
> > >> https://github.com/apache/incubator-mxnet/issues/10856
> > >>
> > >> libomp.so dependency (need REAL fix)
> > >> https://github.com/apache/incubator-mxnet/issues/11417
> > >>
> > >> mxnet-mkl (v0.12.0) crash when using (conda-installed) numpy with MKL
> > >> https://github.com/apache/incubator-mxnet/issues/8532
> > >>
> > >> Performance regression when OMP_NUM_THREADS environment variable is
> not
> > >> set
> > >> https://github.com/apache/incubator-mxnet/issues/9744
> > >>
> > >> Poor concat CPU performance on CUDA builds
> > >> https://github.com/apache/incubator-mxnet/issues/11905
> > >>
> > >> I would appreciate hearing your thoughts.
> > >>
> > >>
> > >> Best
> > >> Anton
> > >>
> > >> [1]
> > >>
> > >>
> >
> https://github.com/apache/incubator-mxnet/blob/master/CMakeLists.txt#L400-L405
> > >> [2] https://github.com/apache/incubator-mxnet/tree/master/3rdparty
> > >> [3] https://github.com/intel/mkl-dnn/blame/master/README.md#L261-L265
> > >> [4] https://github.com/intel/mkl-dnn/blame/master/README.md#L278-L280
> > >> [5] https://software.intel.com/en-us/node/522691
> > >>
> > >
> >
>

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