Re: [Discussion] Remove bundled llvm OpenMP
We are now waiting for a committer's review and merge. ср, 22 мая 2019 г. в 22:14, Pedro Larroy : > Thanks Aaron and Anton! Can we rebase to update the PR? Let me know > how can I help further if you find some problems. > > On Wed, May 22, 2019 at 6:49 AM Aaron Markham > wrote: > > > > I reopened it for you. > > > > On Wed, May 22, 2019, 05:25 Anton Chernov wrote: > > > > > I don't have necessary rights to reopen this PR. > > > > > > пн, 20 мая 2019 г. в 08:00, Pedro Larroy >: > > > > > > > Hi Anton, Stas. > > > > > > > > Can we reopen this PR and get it merged as per the data collected by > > > Stas? > > > > > > > > https://github.com/apache/incubator-mxnet/pull/12160 > > > > > > > > > > > > > > > > https://cwiki.apache.org/confluence/display/MXNET/Benchmarking+MXNet+with+different+OpenMP+implementations > > > > > > > > There are multiple issues that will be fixed by solving this problem. > > > > > > > > > > > > Pedro > > > > > > > > On Tue, Feb 12, 2019 at 4:54 AM Anton Chernov > > > wrote: > > > > > > > > > > I would like to propose a possible alternative solution for > > > > consideration. > > > > > > > > > > If keeping llvm OpenMP as a submodule is inevitable one could make > > > > > following adjustments: > > > > > > > > > > Since compilers try to find their own OpenMP library implicitly, > MXNet > > > > > needs to ensure that only the bundled version is found. Therefore > > > during > > > > > the build and also during deployment this library has to provide > > > symlinks > > > > > for each possible compiler that would link to the built artifact > ie. > > > > > > > > > > libiomp.so -> libgomp.so -> libomp.so > > > > > > > > > > The MKLML iomp would need to be hidden and removed as well. > > > > > > > > > > On Windows it would be a different story, but as can be seen [1] > > > bundled > > > > > OpenMP was not included in the Windows build anyway. > > > > > > > > > > Alternatively: always use iomp (with same symlinking trick though) > > > > provided > > > > > by MKLML distribution [2]. This potentially could work on Windows > as > > > > well. > > > > > > > > > > Best > > > > > Anton > > > > > > > > > > [1] > > > > > > > > > > > > > https://github.com/apache/incubator-mxnet/blob/8a63bdecf2d9f12d34fe5874957ae4c867eb5f5b/CMakeLists.txt#L408-L410 > > > > > [2] https://github.com/intel/mkl-dnn/releases > > > > > > > > > > вт, 12 февр. 2019 г. в 11:22, Anton Chernov : > > > > > > > > > > > Recent benchmarking results have been published here [1]. > Experiments > > > > > > compare different OpenMP implementations as well as binaries > compiled > > > > with > > > > > > different compilers including GCC, Clang and ICC. > > > > > > > > > > > > During experimentation another issues with mixing up libraries > was > > > > > > identified and described here [2]. > > > > > > > > > > > > Best > > > > > > Anton > > > > > > > > > > > > [1] https://cwiki.apache.org/confluence/x/2wclBg > > > > > > [2] > > > > > > > > > > > > > > https://github.com/apache/incubator-mxnet/issues/14087#issuecomment-461734041 > > > > > > > > > > > > > > > > > > вс, 9 дек. 2018 г. в 16:28, Anton Chernov : > > > > > > > > > > > >> Hi Chris, > > > > > >> > > > > > >> Following up on the issue, are all things resolved in the > > > discussion? > > > > > >> > > > > > >> If yes, I kindly ask you to reopen this PR and remove > ‘requesting > > > > > >> changes’ status: > > > > > >> https://github.com/apache/incubator-mxnet/pull/12160 > > > > > >> > > > > > >> Thank you. > > > > > >> > > > > > >> > > > > > >> Best > > > > > >> Anton > > > > > >> > > > > > >> > > > > > >> вт, 27 нояб. 2018 г. в 17:15, Anton Chernov < > mecher...@gmail.com>: > > > > > >> > > > > > >>> Another thing to take into consideration: > > > > > >>> > > > > > >>> All python artefacts that are created (PyPi) are built with > make > > > and > > > > are > > > > > >>> not using the bundled OpenMP library. > > > > > >>> > > > > > >>> One step for the switch to CMake to happen is the approval and > > > > merging > > > > > >>> of the mentioned PR: > > > > > >>> > > > > > >>> https://github.com/apache/incubator-mxnet/pull/12160 > > > > > >>> > > > > > >>> If there are no other objections I kindly ask Chris Olivier to > > > remove > > > > > >>> his 'requesting changes' veto on it to unblock the CMake > overhaul > > > > work. > > > > > >>> > > > > > >>> Thank you. > > > > > >>> > > > > > >>> Best > > > > > >>> Anton > > > > > >>> > > > > > >>> чт, 22 нояб. 2018 г. в 17:11, Anton Chernov < > mecher...@gmail.com>: > > > > > >>> > > > > > > > > > > Thank you for you answer, Chris. > > > > > > > > > > > The whole “mixing omp libraries” is something that occurs in > > > > > production > > > > > every day and certainly in everything that uses mkl. > > > > > > > > > > I'm afraid this statement is wrong. Intel MKL-DNN strictly > ensures > > > > that > > > > > this mixture is not happening: > > > > > > > > > > "Intel MKL-DNN uses OpenMP*
Re: [Discussion] Remove bundled llvm OpenMP
Great! Thank you, Aaron. I have rebased it. ср, 22 мая 2019 г. в 15:49, Aaron Markham : > I reopened it for you. > > On Wed, May 22, 2019, 05:25 Anton Chernov wrote: > > > I don't have necessary rights to reopen this PR. > > > > пн, 20 мая 2019 г. в 08:00, Pedro Larroy : > > > > > Hi Anton, Stas. > > > > > > Can we reopen this PR and get it merged as per the data collected by > > Stas? > > > > > > https://github.com/apache/incubator-mxnet/pull/12160 > > > > > > > > > > > > https://cwiki.apache.org/confluence/display/MXNET/Benchmarking+MXNet+with+different+OpenMP+implementations > > > > > > There are multiple issues that will be fixed by solving this problem. > > > > > > > > > Pedro > > > > > > On Tue, Feb 12, 2019 at 4:54 AM Anton Chernov > > wrote: > > > > > > > > I would like to propose a possible alternative solution for > > > consideration. > > > > > > > > If keeping llvm OpenMP as a submodule is inevitable one could make > > > > following adjustments: > > > > > > > > Since compilers try to find their own OpenMP library implicitly, > MXNet > > > > needs to ensure that only the bundled version is found. Therefore > > during > > > > the build and also during deployment this library has to provide > > symlinks > > > > for each possible compiler that would link to the built artifact ie. > > > > > > > > libiomp.so -> libgomp.so -> libomp.so > > > > > > > > The MKLML iomp would need to be hidden and removed as well. > > > > > > > > On Windows it would be a different story, but as can be seen [1] > > bundled > > > > OpenMP was not included in the Windows build anyway. > > > > > > > > Alternatively: always use iomp (with same symlinking trick though) > > > provided > > > > by MKLML distribution [2]. This potentially could work on Windows as > > > well. > > > > > > > > Best > > > > Anton > > > > > > > > [1] > > > > > > > > > > https://github.com/apache/incubator-mxnet/blob/8a63bdecf2d9f12d34fe5874957ae4c867eb5f5b/CMakeLists.txt#L408-L410 > > > > [2] https://github.com/intel/mkl-dnn/releases > > > > > > > > вт, 12 февр. 2019 г. в 11:22, Anton Chernov : > > > > > > > > > Recent benchmarking results have been published here [1]. > Experiments > > > > > compare different OpenMP implementations as well as binaries > compiled > > > with > > > > > different compilers including GCC, Clang and ICC. > > > > > > > > > > During experimentation another issues with mixing up libraries was > > > > > identified and described here [2]. > > > > > > > > > > Best > > > > > Anton > > > > > > > > > > [1] https://cwiki.apache.org/confluence/x/2wclBg > > > > > [2] > > > > > > > > > > > https://github.com/apache/incubator-mxnet/issues/14087#issuecomment-461734041 > > > > > > > > > > > > > > > вс, 9 дек. 2018 г. в 16:28, Anton Chernov : > > > > > > > > > >> Hi Chris, > > > > >> > > > > >> Following up on the issue, are all things resolved in the > > discussion? > > > > >> > > > > >> If yes, I kindly ask you to reopen this PR and remove ‘requesting > > > > >> changes’ status: > > > > >> https://github.com/apache/incubator-mxnet/pull/12160 > > > > >> > > > > >> Thank you. > > > > >> > > > > >> > > > > >> Best > > > > >> Anton > > > > >> > > > > >> > > > > >> вт, 27 нояб. 2018 г. в 17:15, Anton Chernov >: > > > > >> > > > > >>> Another thing to take into consideration: > > > > >>> > > > > >>> All python artefacts that are created (PyPi) are built with make > > and > > > are > > > > >>> not using the bundled OpenMP library. > > > > >>> > > > > >>> One step for the switch to CMake to happen is the approval and > > > merging > > > > >>> of the mentioned PR: > > > > >>> > > > > >>> https://github.com/apache/incubator-mxnet/pull/12160 > > > > >>> > > > > >>> If there are no other objections I kindly ask Chris Olivier to > > remove > > > > >>> his 'requesting changes' veto on it to unblock the CMake overhaul > > > work. > > > > >>> > > > > >>> Thank you. > > > > >>> > > > > >>> Best > > > > >>> Anton > > > > >>> > > > > >>> чт, 22 нояб. 2018 г. в 17:11, Anton Chernov >: > > > > >>> > > > > > > > > Thank you for you answer, Chris. > > > > > > > > > The whole “mixing omp libraries” is something that occurs in > > > > production > > > > every day and certainly in everything that uses mkl. > > > > > > > > I'm afraid this statement is wrong. Intel MKL-DNN strictly > ensures > > > that > > > > this mixture is not happening: > > > > > > > > "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." > > > > [1] > > > > > > > > That is why 2 different MKLML libraries are provided: > > > > > > > >
Re: [Discussion] Remove bundled llvm OpenMP
Thanks Aaron and Anton! Can we rebase to update the PR? Let me know how can I help further if you find some problems. On Wed, May 22, 2019 at 6:49 AM Aaron Markham wrote: > > I reopened it for you. > > On Wed, May 22, 2019, 05:25 Anton Chernov wrote: > > > I don't have necessary rights to reopen this PR. > > > > пн, 20 мая 2019 г. в 08:00, Pedro Larroy : > > > > > Hi Anton, Stas. > > > > > > Can we reopen this PR and get it merged as per the data collected by > > Stas? > > > > > > https://github.com/apache/incubator-mxnet/pull/12160 > > > > > > > > > > > https://cwiki.apache.org/confluence/display/MXNET/Benchmarking+MXNet+with+different+OpenMP+implementations > > > > > > There are multiple issues that will be fixed by solving this problem. > > > > > > > > > Pedro > > > > > > On Tue, Feb 12, 2019 at 4:54 AM Anton Chernov > > wrote: > > > > > > > > I would like to propose a possible alternative solution for > > > consideration. > > > > > > > > If keeping llvm OpenMP as a submodule is inevitable one could make > > > > following adjustments: > > > > > > > > Since compilers try to find their own OpenMP library implicitly, MXNet > > > > needs to ensure that only the bundled version is found. Therefore > > during > > > > the build and also during deployment this library has to provide > > symlinks > > > > for each possible compiler that would link to the built artifact ie. > > > > > > > > libiomp.so -> libgomp.so -> libomp.so > > > > > > > > The MKLML iomp would need to be hidden and removed as well. > > > > > > > > On Windows it would be a different story, but as can be seen [1] > > bundled > > > > OpenMP was not included in the Windows build anyway. > > > > > > > > Alternatively: always use iomp (with same symlinking trick though) > > > provided > > > > by MKLML distribution [2]. This potentially could work on Windows as > > > well. > > > > > > > > Best > > > > Anton > > > > > > > > [1] > > > > > > > > > https://github.com/apache/incubator-mxnet/blob/8a63bdecf2d9f12d34fe5874957ae4c867eb5f5b/CMakeLists.txt#L408-L410 > > > > [2] https://github.com/intel/mkl-dnn/releases > > > > > > > > вт, 12 февр. 2019 г. в 11:22, Anton Chernov : > > > > > > > > > Recent benchmarking results have been published here [1]. Experiments > > > > > compare different OpenMP implementations as well as binaries compiled > > > with > > > > > different compilers including GCC, Clang and ICC. > > > > > > > > > > During experimentation another issues with mixing up libraries was > > > > > identified and described here [2]. > > > > > > > > > > Best > > > > > Anton > > > > > > > > > > [1] https://cwiki.apache.org/confluence/x/2wclBg > > > > > [2] > > > > > > > > > > https://github.com/apache/incubator-mxnet/issues/14087#issuecomment-461734041 > > > > > > > > > > > > > > > вс, 9 дек. 2018 г. в 16:28, Anton Chernov : > > > > > > > > > >> Hi Chris, > > > > >> > > > > >> Following up on the issue, are all things resolved in the > > discussion? > > > > >> > > > > >> If yes, I kindly ask you to reopen this PR and remove ‘requesting > > > > >> changes’ status: > > > > >> https://github.com/apache/incubator-mxnet/pull/12160 > > > > >> > > > > >> Thank you. > > > > >> > > > > >> > > > > >> Best > > > > >> Anton > > > > >> > > > > >> > > > > >> вт, 27 нояб. 2018 г. в 17:15, Anton Chernov : > > > > >> > > > > >>> Another thing to take into consideration: > > > > >>> > > > > >>> All python artefacts that are created (PyPi) are built with make > > and > > > are > > > > >>> not using the bundled OpenMP library. > > > > >>> > > > > >>> One step for the switch to CMake to happen is the approval and > > > merging > > > > >>> of the mentioned PR: > > > > >>> > > > > >>> https://github.com/apache/incubator-mxnet/pull/12160 > > > > >>> > > > > >>> If there are no other objections I kindly ask Chris Olivier to > > remove > > > > >>> his 'requesting changes' veto on it to unblock the CMake overhaul > > > work. > > > > >>> > > > > >>> Thank you. > > > > >>> > > > > >>> Best > > > > >>> Anton > > > > >>> > > > > >>> чт, 22 нояб. 2018 г. в 17:11, Anton Chernov : > > > > >>> > > > > > > > > Thank you for you answer, Chris. > > > > > > > > > The whole “mixing omp libraries” is something that occurs in > > > > production > > > > every day and certainly in everything that uses mkl. > > > > > > > > I'm afraid this statement is wrong. Intel MKL-DNN strictly ensures > > > that > > > > this mixture is not happening: > > > > > > > > "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." > > > > [1] > > > > > > > > That i
Re: [Discussion] Remove bundled llvm OpenMP
I reopened it for you. On Wed, May 22, 2019, 05:25 Anton Chernov wrote: > I don't have necessary rights to reopen this PR. > > пн, 20 мая 2019 г. в 08:00, Pedro Larroy : > > > Hi Anton, Stas. > > > > Can we reopen this PR and get it merged as per the data collected by > Stas? > > > > https://github.com/apache/incubator-mxnet/pull/12160 > > > > > > > https://cwiki.apache.org/confluence/display/MXNET/Benchmarking+MXNet+with+different+OpenMP+implementations > > > > There are multiple issues that will be fixed by solving this problem. > > > > > > Pedro > > > > On Tue, Feb 12, 2019 at 4:54 AM Anton Chernov > wrote: > > > > > > I would like to propose a possible alternative solution for > > consideration. > > > > > > If keeping llvm OpenMP as a submodule is inevitable one could make > > > following adjustments: > > > > > > Since compilers try to find their own OpenMP library implicitly, MXNet > > > needs to ensure that only the bundled version is found. Therefore > during > > > the build and also during deployment this library has to provide > symlinks > > > for each possible compiler that would link to the built artifact ie. > > > > > > libiomp.so -> libgomp.so -> libomp.so > > > > > > The MKLML iomp would need to be hidden and removed as well. > > > > > > On Windows it would be a different story, but as can be seen [1] > bundled > > > OpenMP was not included in the Windows build anyway. > > > > > > Alternatively: always use iomp (with same symlinking trick though) > > provided > > > by MKLML distribution [2]. This potentially could work on Windows as > > well. > > > > > > Best > > > Anton > > > > > > [1] > > > > > > https://github.com/apache/incubator-mxnet/blob/8a63bdecf2d9f12d34fe5874957ae4c867eb5f5b/CMakeLists.txt#L408-L410 > > > [2] https://github.com/intel/mkl-dnn/releases > > > > > > вт, 12 февр. 2019 г. в 11:22, Anton Chernov : > > > > > > > Recent benchmarking results have been published here [1]. Experiments > > > > compare different OpenMP implementations as well as binaries compiled > > with > > > > different compilers including GCC, Clang and ICC. > > > > > > > > During experimentation another issues with mixing up libraries was > > > > identified and described here [2]. > > > > > > > > Best > > > > Anton > > > > > > > > [1] https://cwiki.apache.org/confluence/x/2wclBg > > > > [2] > > > > > > > https://github.com/apache/incubator-mxnet/issues/14087#issuecomment-461734041 > > > > > > > > > > > > вс, 9 дек. 2018 г. в 16:28, Anton Chernov : > > > > > > > >> Hi Chris, > > > >> > > > >> Following up on the issue, are all things resolved in the > discussion? > > > >> > > > >> If yes, I kindly ask you to reopen this PR and remove ‘requesting > > > >> changes’ status: > > > >> https://github.com/apache/incubator-mxnet/pull/12160 > > > >> > > > >> Thank you. > > > >> > > > >> > > > >> Best > > > >> Anton > > > >> > > > >> > > > >> вт, 27 нояб. 2018 г. в 17:15, Anton Chernov : > > > >> > > > >>> Another thing to take into consideration: > > > >>> > > > >>> All python artefacts that are created (PyPi) are built with make > and > > are > > > >>> not using the bundled OpenMP library. > > > >>> > > > >>> One step for the switch to CMake to happen is the approval and > > merging > > > >>> of the mentioned PR: > > > >>> > > > >>> https://github.com/apache/incubator-mxnet/pull/12160 > > > >>> > > > >>> If there are no other objections I kindly ask Chris Olivier to > remove > > > >>> his 'requesting changes' veto on it to unblock the CMake overhaul > > work. > > > >>> > > > >>> Thank you. > > > >>> > > > >>> Best > > > >>> Anton > > > >>> > > > >>> чт, 22 нояб. 2018 г. в 17:11, Anton Chernov : > > > >>> > > > > > > Thank you for you answer, Chris. > > > > > > > The whole “mixing omp libraries” is something that occurs in > > > production > > > every day and certainly in everything that uses mkl. > > > > > > I'm afraid this statement is wrong. Intel MKL-DNN strictly ensures > > that > > > this mixture is not happening: > > > > > > "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." > > > [1] > > > > > > That is why 2 different MKLML libraries are provided: > > > > > > lib/libmklml_gnu.so | Intel MKL small library for GNU* OpenMP > > runtime > > > lib/libmklml_intel.so | Intel MKL small library for Intel(R) > OpenMP > > > runtime > > > > > > > is the suggestion that libiomp be removed from mkl? > > > > > > That is certainly not my suggestion. > > > > > > > have you spoken with intel? have you consulted Intel at all? > > > >
Re: [Discussion] Remove bundled llvm OpenMP
I don't have necessary rights to reopen this PR. пн, 20 мая 2019 г. в 08:00, Pedro Larroy : > Hi Anton, Stas. > > Can we reopen this PR and get it merged as per the data collected by Stas? > > https://github.com/apache/incubator-mxnet/pull/12160 > > > https://cwiki.apache.org/confluence/display/MXNET/Benchmarking+MXNet+with+different+OpenMP+implementations > > There are multiple issues that will be fixed by solving this problem. > > > Pedro > > On Tue, Feb 12, 2019 at 4:54 AM Anton Chernov wrote: > > > > I would like to propose a possible alternative solution for > consideration. > > > > If keeping llvm OpenMP as a submodule is inevitable one could make > > following adjustments: > > > > Since compilers try to find their own OpenMP library implicitly, MXNet > > needs to ensure that only the bundled version is found. Therefore during > > the build and also during deployment this library has to provide symlinks > > for each possible compiler that would link to the built artifact ie. > > > > libiomp.so -> libgomp.so -> libomp.so > > > > The MKLML iomp would need to be hidden and removed as well. > > > > On Windows it would be a different story, but as can be seen [1] bundled > > OpenMP was not included in the Windows build anyway. > > > > Alternatively: always use iomp (with same symlinking trick though) > provided > > by MKLML distribution [2]. This potentially could work on Windows as > well. > > > > Best > > Anton > > > > [1] > > > https://github.com/apache/incubator-mxnet/blob/8a63bdecf2d9f12d34fe5874957ae4c867eb5f5b/CMakeLists.txt#L408-L410 > > [2] https://github.com/intel/mkl-dnn/releases > > > > вт, 12 февр. 2019 г. в 11:22, Anton Chernov : > > > > > Recent benchmarking results have been published here [1]. Experiments > > > compare different OpenMP implementations as well as binaries compiled > with > > > different compilers including GCC, Clang and ICC. > > > > > > During experimentation another issues with mixing up libraries was > > > identified and described here [2]. > > > > > > Best > > > Anton > > > > > > [1] https://cwiki.apache.org/confluence/x/2wclBg > > > [2] > > > > https://github.com/apache/incubator-mxnet/issues/14087#issuecomment-461734041 > > > > > > > > > вс, 9 дек. 2018 г. в 16:28, Anton Chernov : > > > > > >> Hi Chris, > > >> > > >> Following up on the issue, are all things resolved in the discussion? > > >> > > >> If yes, I kindly ask you to reopen this PR and remove ‘requesting > > >> changes’ status: > > >> https://github.com/apache/incubator-mxnet/pull/12160 > > >> > > >> Thank you. > > >> > > >> > > >> Best > > >> Anton > > >> > > >> > > >> вт, 27 нояб. 2018 г. в 17:15, Anton Chernov : > > >> > > >>> Another thing to take into consideration: > > >>> > > >>> All python artefacts that are created (PyPi) are built with make and > are > > >>> not using the bundled OpenMP library. > > >>> > > >>> One step for the switch to CMake to happen is the approval and > merging > > >>> of the mentioned PR: > > >>> > > >>> https://github.com/apache/incubator-mxnet/pull/12160 > > >>> > > >>> If there are no other objections I kindly ask Chris Olivier to remove > > >>> his 'requesting changes' veto on it to unblock the CMake overhaul > work. > > >>> > > >>> Thank you. > > >>> > > >>> Best > > >>> Anton > > >>> > > >>> чт, 22 нояб. 2018 г. в 17:11, Anton Chernov : > > >>> > > > > Thank you for you answer, Chris. > > > > > The whole “mixing omp libraries” is something that occurs in > > production > > every day and certainly in everything that uses mkl. > > > > I'm afraid this statement is wrong. Intel MKL-DNN strictly ensures > that > > this mixture is not happening: > > > > "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." > > [1] > > > > That is why 2 different MKLML libraries are provided: > > > > lib/libmklml_gnu.so | Intel MKL small library for GNU* OpenMP > runtime > > lib/libmklml_intel.so | Intel MKL small library for Intel(R) OpenMP > > runtime > > > > > is the suggestion that libiomp be removed from mkl? > > > > That is certainly not my suggestion. > > > > > have you spoken with intel? have you consulted Intel at all? > > > > Yes, I have asked for comments on the issue. > > > > > “hard to debug random crash”. you’re seeing an assertion which is > > probably ... > > > > I'm seeing the result of undefined behaviour. And I want to put > > emphasis on the following statement: > > > > I disregards of whether there is a particular reason for the assert > - > > it is
Re: [Discussion] Remove bundled llvm OpenMP
Hi Anton, Stas. Can we reopen this PR and get it merged as per the data collected by Stas? https://github.com/apache/incubator-mxnet/pull/12160 https://cwiki.apache.org/confluence/display/MXNET/Benchmarking+MXNet+with+different+OpenMP+implementations There are multiple issues that will be fixed by solving this problem. Pedro On Tue, Feb 12, 2019 at 4:54 AM Anton Chernov wrote: > > I would like to propose a possible alternative solution for consideration. > > If keeping llvm OpenMP as a submodule is inevitable one could make > following adjustments: > > Since compilers try to find their own OpenMP library implicitly, MXNet > needs to ensure that only the bundled version is found. Therefore during > the build and also during deployment this library has to provide symlinks > for each possible compiler that would link to the built artifact ie. > > libiomp.so -> libgomp.so -> libomp.so > > The MKLML iomp would need to be hidden and removed as well. > > On Windows it would be a different story, but as can be seen [1] bundled > OpenMP was not included in the Windows build anyway. > > Alternatively: always use iomp (with same symlinking trick though) provided > by MKLML distribution [2]. This potentially could work on Windows as well. > > Best > Anton > > [1] > https://github.com/apache/incubator-mxnet/blob/8a63bdecf2d9f12d34fe5874957ae4c867eb5f5b/CMakeLists.txt#L408-L410 > [2] https://github.com/intel/mkl-dnn/releases > > вт, 12 февр. 2019 г. в 11:22, Anton Chernov : > > > Recent benchmarking results have been published here [1]. Experiments > > compare different OpenMP implementations as well as binaries compiled with > > different compilers including GCC, Clang and ICC. > > > > During experimentation another issues with mixing up libraries was > > identified and described here [2]. > > > > Best > > Anton > > > > [1] https://cwiki.apache.org/confluence/x/2wclBg > > [2] > > https://github.com/apache/incubator-mxnet/issues/14087#issuecomment-461734041 > > > > > > вс, 9 дек. 2018 г. в 16:28, Anton Chernov : > > > >> Hi Chris, > >> > >> Following up on the issue, are all things resolved in the discussion? > >> > >> If yes, I kindly ask you to reopen this PR and remove ‘requesting > >> changes’ status: > >> https://github.com/apache/incubator-mxnet/pull/12160 > >> > >> Thank you. > >> > >> > >> Best > >> Anton > >> > >> > >> вт, 27 нояб. 2018 г. в 17:15, Anton Chernov : > >> > >>> Another thing to take into consideration: > >>> > >>> All python artefacts that are created (PyPi) are built with make and are > >>> not using the bundled OpenMP library. > >>> > >>> One step for the switch to CMake to happen is the approval and merging > >>> of the mentioned PR: > >>> > >>> https://github.com/apache/incubator-mxnet/pull/12160 > >>> > >>> If there are no other objections I kindly ask Chris Olivier to remove > >>> his 'requesting changes' veto on it to unblock the CMake overhaul work. > >>> > >>> Thank you. > >>> > >>> Best > >>> Anton > >>> > >>> чт, 22 нояб. 2018 г. в 17:11, Anton Chernov : > >>> > > Thank you for you answer, Chris. > > > The whole “mixing omp libraries” is something that occurs in > production > every day and certainly in everything that uses mkl. > > I'm afraid this statement is wrong. Intel MKL-DNN strictly ensures that > this mixture is not happening: > > "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." > [1] > > That is why 2 different MKLML libraries are provided: > > lib/libmklml_gnu.so | Intel MKL small library for GNU* OpenMP runtime > lib/libmklml_intel.so | Intel MKL small library for Intel(R) OpenMP > runtime > > > is the suggestion that libiomp be removed from mkl? > > That is certainly not my suggestion. > > > have you spoken with intel? have you consulted Intel at all? > > Yes, I have asked for comments on the issue. > > > “hard to debug random crash”. you’re seeing an assertion which is > probably ... > > I'm seeing the result of undefined behaviour. And I want to put > emphasis on the following statement: > > I disregards of whether there is a particular reason for the assert - > it is a result of behaviour that should not happen. There are valid ways > how to use llvm OpenMP in MXNet and the current way is not one of them. > > > The lack of root-causing the problem and knee-jerk solution here > makes me > uncomfortable. > > I hope that my efforts highlighting the problems reach you to mitigate > your uncomfort. >
Re: [Discussion] Remove bundled llvm OpenMP
I would like to propose a possible alternative solution for consideration. If keeping llvm OpenMP as a submodule is inevitable one could make following adjustments: Since compilers try to find their own OpenMP library implicitly, MXNet needs to ensure that only the bundled version is found. Therefore during the build and also during deployment this library has to provide symlinks for each possible compiler that would link to the built artifact ie. libiomp.so -> libgomp.so -> libomp.so The MKLML iomp would need to be hidden and removed as well. On Windows it would be a different story, but as can be seen [1] bundled OpenMP was not included in the Windows build anyway. Alternatively: always use iomp (with same symlinking trick though) provided by MKLML distribution [2]. This potentially could work on Windows as well. Best Anton [1] https://github.com/apache/incubator-mxnet/blob/8a63bdecf2d9f12d34fe5874957ae4c867eb5f5b/CMakeLists.txt#L408-L410 [2] https://github.com/intel/mkl-dnn/releases вт, 12 февр. 2019 г. в 11:22, Anton Chernov : > Recent benchmarking results have been published here [1]. Experiments > compare different OpenMP implementations as well as binaries compiled with > different compilers including GCC, Clang and ICC. > > During experimentation another issues with mixing up libraries was > identified and described here [2]. > > Best > Anton > > [1] https://cwiki.apache.org/confluence/x/2wclBg > [2] > https://github.com/apache/incubator-mxnet/issues/14087#issuecomment-461734041 > > > вс, 9 дек. 2018 г. в 16:28, Anton Chernov : > >> Hi Chris, >> >> Following up on the issue, are all things resolved in the discussion? >> >> If yes, I kindly ask you to reopen this PR and remove ‘requesting >> changes’ status: >> https://github.com/apache/incubator-mxnet/pull/12160 >> >> Thank you. >> >> >> Best >> Anton >> >> >> вт, 27 нояб. 2018 г. в 17:15, Anton Chernov : >> >>> Another thing to take into consideration: >>> >>> All python artefacts that are created (PyPi) are built with make and are >>> not using the bundled OpenMP library. >>> >>> One step for the switch to CMake to happen is the approval and merging >>> of the mentioned PR: >>> >>> https://github.com/apache/incubator-mxnet/pull/12160 >>> >>> If there are no other objections I kindly ask Chris Olivier to remove >>> his 'requesting changes' veto on it to unblock the CMake overhaul work. >>> >>> Thank you. >>> >>> Best >>> Anton >>> >>> чт, 22 нояб. 2018 г. в 17:11, Anton Chernov : >>> Thank you for you answer, Chris. > The whole “mixing omp libraries” is something that occurs in production every day and certainly in everything that uses mkl. I'm afraid this statement is wrong. Intel MKL-DNN strictly ensures that this mixture is not happening: "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." [1] That is why 2 different MKLML libraries are provided: lib/libmklml_gnu.so | Intel MKL small library for GNU* OpenMP runtime lib/libmklml_intel.so | Intel MKL small library for Intel(R) OpenMP runtime > is the suggestion that libiomp be removed from mkl? That is certainly not my suggestion. > have you spoken with intel? have you consulted Intel at all? Yes, I have asked for comments on the issue. > “hard to debug random crash”. you’re seeing an assertion which is probably ... I'm seeing the result of undefined behaviour. And I want to put emphasis on the following statement: I disregards of whether there is a particular reason for the assert - it is a result of behaviour that should not happen. There are valid ways how to use llvm OpenMP in MXNet and the current way is not one of them. > The lack of root-causing the problem and knee-jerk solution here makes me uncomfortable. I hope that my efforts highlighting the problems reach you to mitigate your uncomfort. > 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. I don't want to see performance differences in the current OpenMP library. I want to remove the current OpenMP library and use the one provided by the compiler. Best Anton [1] https://github.com/intel/mkl-dnn/blame/master/README.md#L261-L265 чт, 22 нояб. 2018 г. в 16:50, Chris Olivier : > Do you not work on CI mostly? My apologies for thinking that was some > sort
Re: [Discussion] Remove bundled llvm OpenMP
Recent benchmarking results have been published here [1]. Experiments compare different OpenMP implementations as well as binaries compiled with different compilers including GCC, Clang and ICC. During experimentation another issues with mixing up libraries was identified and described here [2]. Best Anton [1] https://cwiki.apache.org/confluence/x/2wclBg [2] https://github.com/apache/incubator-mxnet/issues/14087#issuecomment-461734041 вс, 9 дек. 2018 г. в 16:28, Anton Chernov : > Hi Chris, > > Following up on the issue, are all things resolved in the discussion? > > If yes, I kindly ask you to reopen this PR and remove ‘requesting changes’ > status: > https://github.com/apache/incubator-mxnet/pull/12160 > > Thank you. > > > Best > Anton > > > вт, 27 нояб. 2018 г. в 17:15, Anton Chernov : > >> Another thing to take into consideration: >> >> All python artefacts that are created (PyPi) are built with make and are >> not using the bundled OpenMP library. >> >> One step for the switch to CMake to happen is the approval and merging of >> the mentioned PR: >> >> https://github.com/apache/incubator-mxnet/pull/12160 >> >> If there are no other objections I kindly ask Chris Olivier to remove his >> 'requesting changes' veto on it to unblock the CMake overhaul work. >> >> Thank you. >> >> Best >> Anton >> >> чт, 22 нояб. 2018 г. в 17:11, Anton Chernov : >> >>> >>> Thank you for you answer, Chris. >>> >>> > The whole “mixing omp libraries” is something that occurs in production >>> every day and certainly in everything that uses mkl. >>> >>> I'm afraid this statement is wrong. Intel MKL-DNN strictly ensures that >>> this mixture is not happening: >>> >>> "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." >>> [1] >>> >>> That is why 2 different MKLML libraries are provided: >>> >>> lib/libmklml_gnu.so | Intel MKL small library for GNU* OpenMP runtime >>> lib/libmklml_intel.so | Intel MKL small library for Intel(R) OpenMP >>> runtime >>> >>> > is the suggestion that libiomp be removed from mkl? >>> >>> That is certainly not my suggestion. >>> >>> > have you spoken with intel? have you consulted Intel at all? >>> >>> Yes, I have asked for comments on the issue. >>> >>> > “hard to debug random crash”. you’re seeing an assertion which is >>> probably ... >>> >>> I'm seeing the result of undefined behaviour. And I want to put emphasis >>> on the following statement: >>> >>> I disregards of whether there is a particular reason for the assert - it >>> is a result of behaviour that should not happen. There are valid ways how >>> to use llvm OpenMP in MXNet and the current way is not one of them. >>> >>> > The lack of root-causing the problem and knee-jerk solution here makes >>> me >>> uncomfortable. >>> >>> I hope that my efforts highlighting the problems reach you to mitigate >>> your uncomfort. >>> >>> > 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. >>> >>> I don't want to see performance differences in the current OpenMP >>> library. I want to remove the current OpenMP library and use the one >>> provided by the compiler. >>> >>> >>> >>> Best >>> Anton >>> >>> [1] https://github.com/intel/mkl-dnn/blame/master/README.md#L261-L265 >>> >>> чт, 22 нояб. 2018 г. в 16:50, Chris Olivier : >>> 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 debu
Re: [Discussion] Remove bundled llvm OpenMP
Hi Chris, Following up on the issue, are all things resolved in the discussion? If yes, I kindly ask you to reopen this PR and remove ‘requesting changes’ status: https://github.com/apache/incubator-mxnet/pull/12160 Thank you. Best Anton вт, 27 нояб. 2018 г. в 17:15, Anton Chernov : > Another thing to take into consideration: > > All python artefacts that are created (PyPi) are built with make and are > not using the bundled OpenMP library. > > One step for the switch to CMake to happen is the approval and merging of > the mentioned PR: > > https://github.com/apache/incubator-mxnet/pull/12160 > > If there are no other objections I kindly ask Chris Olivier to remove his > 'requesting changes' veto on it to unblock the CMake overhaul work. > > Thank you. > > Best > Anton > > чт, 22 нояб. 2018 г. в 17:11, Anton Chernov : > >> >> Thank you for you answer, Chris. >> >> > The whole “mixing omp libraries” is something that occurs in production >> every day and certainly in everything that uses mkl. >> >> I'm afraid this statement is wrong. Intel MKL-DNN strictly ensures that >> this mixture is not happening: >> >> "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." >> [1] >> >> That is why 2 different MKLML libraries are provided: >> >> lib/libmklml_gnu.so | Intel MKL small library for GNU* OpenMP runtime >> lib/libmklml_intel.so | Intel MKL small library for Intel(R) OpenMP >> runtime >> >> > is the suggestion that libiomp be removed from mkl? >> >> That is certainly not my suggestion. >> >> > have you spoken with intel? have you consulted Intel at all? >> >> Yes, I have asked for comments on the issue. >> >> > “hard to debug random crash”. you’re seeing an assertion which is >> probably ... >> >> I'm seeing the result of undefined behaviour. And I want to put emphasis >> on the following statement: >> >> I disregards of whether there is a particular reason for the assert - it >> is a result of behaviour that should not happen. There are valid ways how >> to use llvm OpenMP in MXNet and the current way is not one of them. >> >> > The lack of root-causing the problem and knee-jerk solution here makes >> me >> uncomfortable. >> >> I hope that my efforts highlighting the problems reach you to mitigate >> your uncomfort. >> >> > 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. >> >> I don't want to see performance differences in the current OpenMP >> library. I want to remove the current OpenMP library and use the one >> provided by the compiler. >> >> >> >> Best >> Anton >> >> [1] https://github.com/intel/mkl-dnn/blame/master/README.md#L261-L265 >> >> чт, 22 нояб. 2018 г. в 16:50, Chris Olivier : >> >>> 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. >>> >>>
Re: [Discussion] Remove bundled llvm OpenMP
Another thing to take into consideration: All python artefacts that are created (PyPi) are built with make and are not using the bundled OpenMP library. One step for the switch to CMake to happen is the approval and merging of the mentioned PR: https://github.com/apache/incubator-mxnet/pull/12160 If there are no other objections I kindly ask Chris Olivier to remove his 'requesting changes' veto on it to unblock the CMake overhaul work. Thank you. Best Anton чт, 22 нояб. 2018 г. в 17:11, Anton Chernov : > > Thank you for you answer, Chris. > > > The whole “mixing omp libraries” is something that occurs in production > every day and certainly in everything that uses mkl. > > I'm afraid this statement is wrong. Intel MKL-DNN strictly ensures that > this mixture is not happening: > > "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." [1] > > That is why 2 different MKLML libraries are provided: > > lib/libmklml_gnu.so | Intel MKL small library for GNU* OpenMP runtime > lib/libmklml_intel.so | Intel MKL small library for Intel(R) OpenMP runtime > > > is the suggestion that libiomp be removed from mkl? > > That is certainly not my suggestion. > > > have you spoken with intel? have you consulted Intel at all? > > Yes, I have asked for comments on the issue. > > > “hard to debug random crash”. you’re seeing an assertion which is > probably ... > > I'm seeing the result of undefined behaviour. And I want to put emphasis > on the following statement: > > I disregards of whether there is a particular reason for the assert - it > is a result of behaviour that should not happen. There are valid ways how > to use llvm OpenMP in MXNet and the current way is not one of them. > > > The lack of root-causing the problem and knee-jerk solution here makes me > uncomfortable. > > I hope that my efforts highlighting the problems reach you to mitigate > your uncomfort. > > > 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. > > I don't want to see performance differences in the current OpenMP library. > I want to remove the current OpenMP library and use the one provided by the > compiler. > > > > Best > Anton > > [1] https://github.com/intel/mkl-dnn/blame/master/README.md#L261-L265 > > чт, 22 нояб. 2018 г. в 16:50, Chris Olivier : > >> 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 >> 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
Re: [Discussion] Remove bundled llvm OpenMP
Thank you for you answer, Chris. > The whole “mixing omp libraries” is something that occurs in production every day and certainly in everything that uses mkl. I'm afraid this statement is wrong. Intel MKL-DNN strictly ensures that this mixture is not happening: "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." [1] That is why 2 different MKLML libraries are provided: lib/libmklml_gnu.so | Intel MKL small library for GNU* OpenMP runtime lib/libmklml_intel.so | Intel MKL small library for Intel(R) OpenMP runtime > is the suggestion that libiomp be removed from mkl? That is certainly not my suggestion. > have you spoken with intel? have you consulted Intel at all? Yes, I have asked for comments on the issue. > “hard to debug random crash”. you’re seeing an assertion which is probably ... I'm seeing the result of undefined behaviour. And I want to put emphasis on the following statement: I disregards of whether there is a particular reason for the assert - it is a result of behaviour that should not happen. There are valid ways how to use llvm OpenMP in MXNet and the current way is not one of them. > The lack of root-causing the problem and knee-jerk solution here makes me uncomfortable. I hope that my efforts highlighting the problems reach you to mitigate your uncomfort. > 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. I don't want to see performance differences in the current OpenMP library. I want to remove the current OpenMP library and use the one provided by the compiler. Best Anton [1] https://github.com/intel/mkl-dnn/blame/master/README.md#L261-L265 чт, 22 нояб. 2018 г. в 16:50, Chris Olivier : > 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 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. > > > >
Re: [Discussion] Remove bundled llvm OpenMP
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 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 : > > > 3x less overhead* > > > > On Thu, Nov 22, 2018 at 6:25 AM Chris Olivier > > 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 > > 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/t
Re: [Discussion] Remove bundled llvm OpenMP
The proposal here is not to eliminate the use of OpenMP but rather to use the compiler's OpenMP implementation rather than a bundled one. I've been bitten by issues with having multiple linked OpenMP implementations before in another library and it was extremely difficult to debug. It seems to me that tackling the issue with the assert is an orthogonal issue altogether. --Alfredo Luque Software Engineer Airbnb Machine Learning Infrastructure On Thu, Nov 22, 2018 at 10:12 AM Anton Chernov 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 : > > > 3x less overhead* > > > > On Thu, Nov 22, 2018 at 6:25 AM Chris Olivier > > 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 > > 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 librari
Re: [Discussion] Remove bundled llvm OpenMP
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 : > 3x less overhead* > > On Thu, Nov 22, 2018 at 6:25 AM Chris Olivier > 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 > 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 > >> (0x7f697bc55000) > >> libgomp.so.1 => /usr/lib/x86_64-linux-gnu/libgomp.so.1 > >> (0x7f69660cd000) > >> > >> *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 t
Re: [Discussion] Remove bundled llvm OpenMP
3x less overhead* On Thu, Nov 22, 2018 at 6:25 AM Chris Olivier 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 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 >> (0x7f697bc55000) >> libgomp.so.1 => /usr/lib/x86_64-linux-gnu/libgomp.so.1 >> (0x7f69660cd000) >> >> *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
Re: [Discussion] Remove bundled llvm OpenMP
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 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 > (0x7f697bc55000) > libgomp.so.1 => /usr/lib/x86_64-linux-gnu/libgomp.so.1 > (0x7f69660cd000) > > *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
RE: [Discussion] Remove bundled llvm OpenMP
Thanks for the great summary, Anton. I'm curious that is there anybody builds mxnet successfully with ICC/ICPC? -Original Message- From: Anton Chernov [mailto:mecher...@gmail.com] Sent: Thursday, November 22, 2018 8:36 PM To: d...@mxnet.apache.org Subject: [Discussion] Remove bundled llvm OpenMP 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 (0x7f697bc55000) libgomp.so.1 => /usr/lib/x86_64-linux-gnu/libgomp.so.1 (0x7f69660cd000) *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
