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 regular calls. Some common questions are answered in the FAQ.

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

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.

Q: How to build an OpenMP 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.

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.

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.

Q: Does OpenMP offloading support work in pre-packaged LLVM releases?

For now, the answer is most likely no. Please see Q: How to build an OpenMP 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 Q: How to build an OpenMP offload capable compiler?.

Q: Does Clang support <math.h> and <complex.h> 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 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.

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.