Support, Getting Involved, and FAQ ================================== Please do not hesitate to reach out to us via openmp-dev@lists.llvm.org or join one of our :ref:`regular calls `. Some common questions are answered in the :ref:`faq`. .. _calls: Calls ----- OpenMP in LLVM Technical Call ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ - Development updates on OpenMP (and OpenACC) in the LLVM Project, including Clang, optimization, and runtime work. - Join `OpenMP in LLVM Technical Call `__. - Time: Weekly call on every Wednesday 7:00 AM Pacific time. - Meeting minutes are `here `__. - Status tracking `page `__. OpenMP in Flang Technical Call ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ - Development updates on OpenMP and OpenACC in the Flang Project. - Join `OpenMP in Flang Technical Call `_ - Time: Weekly call on every Thursdays 8:00 AM Pacific time. - Meeting minutes are `here `__. - Status tracking `page `__. .. _faq: FAQ --- .. note:: The FAQ is a work in progress and most of the expected content is not yet available. While you can expect changes, we always welcome feedback and additions. Please contact, e.g., through ``openmp-dev@lists.llvm.org``. Q: How to contribute a patch to the webpage or any other part? ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ All patches go through the regular `LLVM review process `_. .. _build_offload_capable_compiler: Q: How to build an OpenMP GPU offload capable compiler? ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ To build an *effective* OpenMP offload capable compiler, only one extra CMake option, `LLVM_ENABLE_RUNTIMES="openmp"`, is needed when building LLVM (Generic information about building LLVM is available `here `__.). Make sure all backends that are targeted by OpenMP to be enabled. By default, Clang will be built with all backends enabled. When building with `LLVM_ENABLE_RUNTIMES="openmp"` OpenMP should not be enabled in `LLVM_ENABLE_PROJECTS` because it is enabled by default. For Nvidia offload, please see :ref:`build_nvidia_offload_capable_compiler`. For AMDGPU offload, please see :ref:`build_amdgpu_offload_capable_compiler`. .. note:: The compiler that generates the offload code should be the same (version) as the compiler that builds the OpenMP device runtimes. The OpenMP host runtime can be built by a different compiler. .. _advanced_builds: https://llvm.org//docs/AdvancedBuilds.html .. _build_nvidia_offload_capable_compiler: Q: How to build an OpenMP NVidia offload capable compiler? ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ The Cuda SDK is required on the machine that will execute the openmp application. If your build machine is not the target machine or automatic detection of the available GPUs failed, you should also set: - `CLANG_OPENMP_NVPTX_DEFAULT_ARCH=sm_XX` where `XX` is the architecture of your GPU, e.g, 80. - `LIBOMPTARGET_NVPTX_COMPUTE_CAPABILITIES=YY` where `YY` is the numeric compute capacity of your GPU, e.g., 75. .. _build_amdgpu_offload_capable_compiler: Q: How to build an OpenMP AMDGPU offload capable compiler? ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ A subset of the `ROCm `_ toolchain is required to build the LLVM toolchain and to execute the openmp application. Either install ROCm somewhere that cmake's find_package can locate it, or build the required subcomponents ROCt and ROCr from source. The two components used are ROCT-Thunk-Interface, roct, and ROCR-Runtime, rocr. Roct is the userspace part of the linux driver. It calls into the driver which ships with the linux kernel. It is an implementation detail of Rocr from OpenMP's perspective. Rocr is an implementation of `HSA `_. .. code-block:: text SOURCE_DIR=same-as-llvm-source # e.g. the checkout of llvm-project, next to openmp BUILD_DIR=somewhere INSTALL_PREFIX=same-as-llvm-install cd $SOURCE_DIR git clone git@github.com:RadeonOpenCompute/ROCT-Thunk-Interface.git -b roc-4.2.x \ --single-branch git clone git@github.com:RadeonOpenCompute/ROCR-Runtime.git -b rocm-4.2.x \ --single-branch cd $BUILD_DIR && mkdir roct && cd roct cmake $SOURCE_DIR/ROCT-Thunk-Interface/ -DCMAKE_INSTALL_PREFIX=$INSTALL_PREFIX \ -DCMAKE_BUILD_TYPE=Release -DBUILD_SHARED_LIBS=OFF make && make install cd $BUILD_DIR && mkdir rocr && cd rocr cmake $SOURCE_DIR/ROCR-Runtime/src -DIMAGE_SUPPORT=OFF \ -DCMAKE_INSTALL_PREFIX=$INSTALL_PREFIX -DCMAKE_BUILD_TYPE=Release \ -DBUILD_SHARED_LIBS=ON make && make install ``IMAGE_SUPPORT`` requires building rocr with clang and is not used by openmp. Provided cmake's find_package can find the ROCR-Runtime package, LLVM will build a tool ``bin/amdgpu-arch`` which will print a string like ``gfx906`` when run if it recognises a GPU on the local system. LLVM will also build a shared library, libomptarget.rtl.amdgpu.so, which is linked against rocr. With those libraries installed, then LLVM build and installed, try: .. code-block:: shell clang -O2 -fopenmp -fopenmp-targets=amdgcn-amd-amdhsa example.c -o example && ./example Q: What are the known limitations of OpenMP AMDGPU offload? ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ LD_LIBRARY_PATH or rpath/runpath are required to find libomp.so and libomptarget.so There is no libc. That is, malloc and printf do not exist. Libm is implemented in terms of the rocm device library, which will be searched for if linking with '-lm'. Some versions of the driver for the radeon vii (gfx906) will error unless the environment variable 'export HSA_IGNORE_SRAMECC_MISREPORT=1' is set. It is a recent addition to LLVM and the implementation differs from that which has been shipping in ROCm and AOMP for some time. Early adopters will encounter bugs. Q: What are the LLVM components used in offloading and how are they found? ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ The libraries used by an executable compiled for target offloading are: - ``libomp.so`` (or similar), the host openmp runtime - ``libomptarget.so``, the target-agnostic target offloading openmp runtime - plugins loaded by libomptarget.so: - ``libomptarget.rtl.amdgpu.so`` - ``libomptarget.rtl.cuda.so`` - ``libomptarget.rtl.x86_64.so`` - ``libomptarget.rtl.ve.so`` - and others - dependencies of those plugins, e.g. cuda/rocr for nvptx/amdgpu The compiled executable is dynamically linked against a host runtime, e.g. ``libomp.so``, and against the target offloading runtime, ``libomptarget.so``. These are found like any other dynamic library, by setting rpath or runpath on the executable, by setting ``LD_LIBRARY_PATH``, or by adding them to the system search. ``libomptarget.so`` has rpath or runpath (whichever the system default is) set to ``$ORIGIN``, and the plugins are located next to it, so it will find the plugins without any environment variables set. If ``LD_LIBRARY_PATH`` is set, whether it overrides which plugin is found depends on whether your system treats ``-Wl,-rpath`` as RPATH or RUNPATH. The plugins will try to find their dependencies in plugin-dependent fashion. The cuda plugin is dynamically linked against libcuda if cmake found it at compiler build time. Otherwise it will attempt to dlopen ``libcuda.so``. It does not have rpath set. The amdgpu plugin is linked against ROCr if cmake found it at compiler build time. Otherwise it will attempt to dlopen ``libhsa-runtime64.so``. It has rpath set to ``$ORIGIN``, so installing ``libhsa-runtime64.so`` in the same directory is a way to locate it without environment variables. In addition to those, there is a compiler runtime library called deviceRTL. This is compiled from mostly common code into an architecture specific bitcode library, e.g. ``libomptarget-nvptx-sm_70.bc``. Clang and the deviceRTL need to match closely as the interface between them changes frequently. Using both from the same monorepo checkout is strongly recommended. Unlike the host side which lets environment variables select components, the deviceRTL that is located in the clang lib directory is preferred. Only if it is absent, the ``LIBRARY_PATH`` environment variable is searched to find a bitcode file with the right name. This can be overridden by passing a clang flag, ``--libomptarget-nvptx-bc-path`` or ``--libomptarget-amdgcn-bc-path``. That can specify a directory or an exact bitcode file to use. Q: Does OpenMP offloading support work in pre-packaged LLVM releases? ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ For now, the answer is most likely *no*. Please see :ref:`build_offload_capable_compiler`. Q: Does OpenMP offloading support work in packages distributed as part of my OS? ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ For now, the answer is most likely *no*. Please see :ref:`build_offload_capable_compiler`. .. _math_and_complex_in_target_regions: Q: Does Clang support `` and `` operations in OpenMP target on GPUs? ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Yes, LLVM/Clang allows math functions and complex arithmetic inside of OpenMP target regions that are compiled for GPUs. Clang provides a set of wrapper headers that are found first when `math.h` and `complex.h`, for C, `cmath` and `complex`, for C++, or similar headers are included by the application. These wrappers will eventually include the system version of the corresponding header file after setting up a target device specific environment. The fact that the system header is included is important because they differ based on the architecture and operating system and may contain preprocessor, variable, and function definitions that need to be available in the target region regardless of the targeted device architecture. However, various functions may require specialized device versions, e.g., `sin`, and others are only available on certain devices, e.g., `__umul64hi`. To provide "native" support for math and complex on the respective architecture, Clang will wrap the "native" math functions, e.g., as provided by the device vendor, in an OpenMP begin/end declare variant. These functions will then be picked up instead of the host versions while host only variables and function definitions are still available. Complex arithmetic and functions are support through a similar mechanism. It is worth noting that this support requires `extensions to the OpenMP begin/end declare variant context selector `__ that are exposed through LLVM/Clang to the user as well. Q: What is a way to debug errors from mapping memory to a target device? ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ An experimental way to debug these errors is to use :ref:`remote process offloading `. By using ``libomptarget.rtl.rpc.so`` and ``openmp-offloading-server``, it is possible to explicitly perform memory transfers between processes on the host CPU and run sanitizers while doing so in order to catch these errors. Q: Why does my application say "Named symbol not found" and abort when I run it? ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ This is most likely caused by trying to use OpenMP offloading with static libraries. Static libraries do not contain any device code, so when the runtime attempts to execute the target region it will not be found and you will get an an error like this. .. code-block:: text CUDA error: Loading '__omp_offloading_fd02_3231c15__Z3foov_l2' Failed CUDA error: named symbol not found Libomptarget error: Unable to generate entries table for device id 0. Currently, the only solution is to change how the application is built and avoid the use of static libraries. Q: Can I use dynamically linked libraries with OpenMP offloading? ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Dynamically linked libraries can be only used if there is no device code split between the library and application. Anything declared on the device inside the shared library will not be visible to the application when it's linked. Q: How to build an OpenMP offload capable compiler with an outdated host compiler? ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Enabling the OpenMP runtime will perform a two-stage build for you. If your host compiler is different from your system-wide compiler, you may need to set the CMake variable `GCC_INSTALL_PREFIX` so clang will be able to find the correct GCC toolchain in the second stage of the build. For example, if your system-wide GCC installation is too old to build LLVM and you would like to use a newer GCC, set the CMake variable `GCC_INSTALL_PREFIX` to inform clang of the GCC installation you would like to use in the second stage. Q: How can I include OpenMP offloading support in my CMake project? ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Currently, there is an experimental CMake find module for OpenMP target offloading provided by LLVM. It will attempt to find OpenMP target offloading support for your compiler. The flags necessary for OpenMP target offloading will be loaded into the ``OpenMPTarget::OpenMPTarget_`` target or the ``OpenMPTarget__FLAGS`` variable if successful. Currently supported devices are ``AMDGPU`` and ``NVPTX``. To use this module, simply add the path to CMake's current module path and call ``find_package``. The module will be installed with your OpenMP installation by default. Including OpenMP offloading support in an application should now only require a few additions. .. code-block:: cmake cmake_minimum_required(VERSION 3.13.4) project(offloadTest VERSION 1.0 LANGUAGES CXX) list(APPEND CMAKE_MODULE_PATH "${PATH_TO_OPENMP_INSTALL}/lib/cmake/openmp") find_package(OpenMPTarget REQUIRED NVPTX) add_executable(offload) target_link_libraries(offload PRIVATE OpenMPTarget::OpenMPTarget_NVPTX) target_sources(offload PRIVATE ${CMAKE_CURRENT_SOURCE_DIR}/src/Main.cpp) Using this module requires at least CMake version 3.13.4. Supported languages are C and C++ with Fortran support planned in the future. Compiler support is best for Clang but this module should work for other compiler vendors such as IBM, GNU.