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LB4OMP is an extended LLVM OpenMP runtime library that supports thirteen dynamic and adaptive loop scheduling techniques from the literature.

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LB4OMP

LB4OMP is an extended LLVM OpenMP runtime library that supports thirteen dynamic and adaptive loop scheduling techniques from the literature. LB4OMP is a load balancing performance portfolio that can offer improved performance by adapting to the unpredictable variations in application and system during execution. LB4OMP is used to improve applications performance, assess the effectiveness of loop scheduling techniques, and support loop scheduling research in multithreaded applications.

Paper references

  • [J. H. M. Korndörfer, A. Eleliemy, A. Mohammed and F. M. Ciorba, LB4OMP: A Dynamic Load Balancing Library for Multithreaded Applications, in IEEE Transactions on Parallel and Distributed Systems, vol. 33, no. 4, pp. 830-841, doi: 10.1109/TPDS.2021.3107775.](https://ieeexplore.ieee.org/document/9524500/)

LB4OMP contains the following loop scheduling techniques:

OpenMP standard

static
dynamic

guided

Dynamic and non-adaptive loop scheduling techniques OpenMP non-standard

Trapezoid self scheduling (TSS)

Dynamic and non-adaptive loop scheduling techniques newly implemented in LB4OMP

Fixed size chunk (FSC)
Factoring (FAC)
Improved implementation of Factoring (mFAC)
Practical variant of factoring (FAC2)
Practical variant of weighted factoring (WF2)
Tapering (TAP)
Modified Fixed size chunk (mFSC)
Trapezoid factoring self scheduling (TFSS)
Fixed increase self scheduling (FISS)
Variable increase self scheduling (FISS)

Random (RND)

Dynamic and adaptive loop scheduling techniques newly implemented in LB4OMP

BOLD
Adaptive weighted factoring (AWF) for time-stepping applications
Four variants of adaptive weighted factoring (AWF-B,C,D,E)
Adaptive factoring (AF)

Improved implementation of Adaptive factoring (mAF)

LB4OMP contains the following features for performance measurement:

profiling

The profiling tool works similar to dynamic,1, yet with timers that capture the average iteration execution time and its standard deviation for the target loops. The collected information is stored in a file, which is read later by the FSC, FAC, TAP, and BOLD during execution.

How to use LB4OMP

The first step is to compile the runtime library. LB4OMP is compiled using the same guidelines provided by the LLVM OpenMP runtime library as shown in the next section of this README (How to Build LB4OMP, the extended LLVM* OpenMP* Libraries).

One must ensure that the target OpenMP loops in the application contain the schedule(runtime) clause. If that is the case, no other changes are required and there is no need to recompile the application code.

Sequentially, one needs to add the path to the compiled LB4OMP runtime library to the environment variable that the linker uses to load dynamic and shared libraries. For instance, in Linux/Unix environments, one adds the path for the compiled LB4OMP to the LD_LIBRARY_PATH environment variable.

LB4OMP introduces specific environment variables that need to be defined to select and control the provided scheduling techniques. These are:

KMP_CPU_SPEED informs LB4OMP about the host CPU speed in MHz. Defining this variable is mandatory, because the timing functions of LB4OMP use it. Only integer values are expected for this environment variable.

KMP_PROFILE_DATA defines the path for the profiling information. Four techniques: FSC, FAC, TAP, and BOLD require profiling information, such as the average of loop iteration execution times, the standard deviation of loop iteration execution times, and the scheduling overhead of self-scheduling (individual) loop iterations. LB4OMP implements a profiling tool that collects such information. The profiling tool uses KMP_PROFILE_DATA to determine the path where the collected profiling information will be stored.

KMP_WEIGHTS can be used by WF2, AWF, or AWF-B,C,D,E. It expects a sequence of values separated by commas. These values denote the weights that each core will receive. The weights are used, for example, for heterogeneous systems if one wants to give fewer iterations to slower cores. For instance, if the weights are set as {1,0.5}, the second core will receive half of the chunk size that the first core received. The default KMP_WEIGHTS value is 1 for all cores.

KMP_TIME_LOOPS defines the path where LB4OMP stores the collected execution time of all OpenMP parallel loops associated with the schedule(runtime) clause. When this environment variable is not defined, LB4OMP will not collect loops' execution time.

KMP_PRINT_CHUNKS when this environment variable is set to one, the LB4OMP collects and stores the calculated chunk size for each thread for each scheduling round. This information is stored in the same file as defined by KMP_TIME_LOOPS. This data may be very large depending on the scheduling technique and the size of the OpenMP loop.

How to Build LB4OMP, the extended LLVM* OpenMP* Libraries

Adopted from the official LLVM repository README.rst

This repository requires CMake v2.8.0 or later. LLVM and Clang need a more recent version which also applies for in-tree builds. For more information than available in this document please see LLVM's CMake documentation and the official documentation.

  • When calling CMake for the first time, all needed compiler options must be specified on the command line. After this initial call to CMake, the compiler definitions must not be included for further calls to CMake. Other options can be specified on the command line multiple times including all definitions in the build options section below.

  • Example of configuring, building, reconfiguring, rebuilding:

    $ mkdir build
    $ cd build
    $ cmake -DCMAKE_C_COMPILER=icc -DCMAKE_CXX_COMPILER=icpc -DLIBOMP_HAVE___RDTSC=ON -DLIBOMP_HAVE_X86INTRIN_H=ON ..
    $ make
    $ mkdir build
    $ cd build
    $ cmake -DCMAKE_C_COMPILER=clang -DCMAKE_CXX_COMPILER=clang++ ..  # Initial configuration
    $ make
    ...
    $ make clean
    $ cmake -DCMAKE_BUILD_TYPE=Debug ..                               # Second configuration
    $ make
    ...
    $ rm -rf *
    $ cmake -DCMAKE_C_COMPILER=gcc -DCMAKE_CXX_COMPILER=g++ ..        # Third configuration
    $ make
  • Notice in the example how the compiler definitions are only specified for an empty build directory, but other build options are used at any time.

  • The file CMakeCache.txt which is created after the first call to CMake is a configuration file which holds all values for the build options. These values can be changed using a text editor to modify CMakeCache.txt as opposed to using definitions on the command line.

  • To have CMake create a particular type of build generator file simply include the -G <Generator name> option:

    $ cmake -G "Unix Makefiles" ...

    You can see a list of generators CMake supports by executing the cmake command with no arguments.

$ cd openmp_top_level/ [ this directory with libomptarget/, runtime/, etc. ]
$ mkdir build
$ cd build

[ Unix* Libraries ]
$ cmake -DCMAKE_C_COMPILER=<C Compiler> -DCMAKE_CXX_COMPILER=<C++ Compiler> ..

[ Windows* Libraries ]
$ cmake -G <Generator Type> -DCMAKE_C_COMPILER=<C Compiler> -DCMAKE_CXX_COMPILER=<C++ Compiler> -DCMAKE_ASM_MASM_COMPILER=[ml | ml64] -DCMAKE_BUILD_TYPE=Release ..

$ make
$ make install

Builds with CMake can be customized by means of options as already seen above. One possibility is to pass them via the command line:

$ cmake -DOPTION=<value> path/to/source

Note

The first value listed is the respective default for that option.

For full documentation consult the CMake manual or execute cmake --help-variable VARIABLE_NAME to get information about a specific variable.

CMAKE_BUILD_TYPE = Release|Debug|RelWithDebInfo
Build type can be Release, Debug, or RelWithDebInfo which chooses the optimization level and presence of debugging symbols.
CMAKE_C_COMPILER = <C compiler name>
Specify the C compiler.
CMAKE_CXX_COMPILER = <C++ compiler name>
Specify the C++ compiler.
CMAKE_Fortran_COMPILER = <Fortran compiler name>
Specify the Fortran compiler. This option is only needed when LIBOMP_FORTRAN_MODULES is ON (see below). So typically, a Fortran compiler is not needed during the build.
CMAKE_ASM_MASM_COMPILER = ml|ml64
This option is only relevant for Windows*.
OPENMP_ENABLE_WERROR = OFF|ON
Treat warnings as errors and fail, if a compiler warning is triggered.
OPENMP_LIBDIR_SUFFIX = ""
Extra suffix to append to the directory where libraries are to be installed.
OPENMP_TEST_C_COMPILER = ${CMAKE_C_COMPILER}
Compiler to use for testing. Defaults to the compiler that was also used for building.
OPENMP_TEST_CXX_COMPILER = ${CMAKE_CXX_COMPILER}
Compiler to use for testing. Defaults to the compiler that was also used for building.
OPENMP_LLVM_TOOLS_DIR = /path/to/built/llvm/tools
Additional path to search for LLVM tools needed by tests.
OPENMP_LLVM_LIT_EXECUTABLE = /path/to/llvm-lit
Specify full path to llvm-lit executable for running tests. The default is to search the PATH and the directory in OPENMP_LLVM_TOOLS_DIR.
OPENMP_FILECHECK_EXECUTABLE = /path/to/FileCheck
Specify full path to FileCheck executable for running tests. The default is to search the PATH and the directory in OPENMP_LLVM_TOOLS_DIR.
LIBOMP_ARCH = aarch64|arm|i386|mic|mips|mips64|ppc64|ppc64le|x86_64
The default value for this option is chosen based on probing the compiler for architecture macros (e.g., is __x86_64__ predefined by compiler?).
LIBOMP_MIC_ARCH = knc|knf
Intel(R) Many Integrated Core Architecture (Intel(R) MIC Architecture) to build for. This value is ignored if LIBOMP_ARCH does not equal mic.
LIBOMP_OMP_VERSION = 50|45|40|30
OpenMP version to build for. Older versions will disable certain functionality and entry points.
LIBOMP_LIB_TYPE = normal|profile|stubs
Library type can be normal, profile, or stubs.
LIBOMP_USE_VERSION_SYMBOLS = ON|OFF
Use versioned symbols for building the library. This option only makes sense for ELF based libraries where version symbols are supported (Linux*, some BSD* variants). It is OFF by default for Windows* and macOS*, but ON for other Unix based operating systems.
LIBOMP_ENABLE_SHARED = ON|OFF

Build a shared library. If this option is OFF, static OpenMP libraries will be built instead of dynamic ones.

Note

Static libraries are not supported on Windows*.

LIBOMP_FORTRAN_MODULES = OFF|ON
Create the Fortran modules (requires Fortran compiler).

On macOS* machines, it is possible to build universal (or fat) libraries which include both i386 and x86_64 architecture objects in a single archive.

$ cmake -DCMAKE_C_COMPILER=clang -DCMAKE_CXX_COMPILER=clang++ -DCMAKE_OSX_ARCHITECTURES='i386;x86_64' ..
$ make

There is also an option LIBOMP_OSX_ARCHITECTURES which can be set in case this is an LLVM source tree build. It will only apply for the libomp library avoids having the entire LLVM/Clang build produce universal binaries.

LIBOMP_USE_ADAPTIVE_LOCKS = ON|OFF
Include adaptive locks, based on Intel(R) Transactional Synchronization Extensions (Intel(R) TSX). This feature is x86 specific and turned ON by default for IA-32 architecture and Intel(R) 64 architecture.
LIBOMP_USE_INTERNODE_ALIGNMENT = OFF|ON
Align certain data structures on 4096-byte. This option is useful on multi-node systems where a small CACHE_LINE setting leads to false sharing.
LIBOMP_OMPT_SUPPORT = ON|OFF
Include support for the OpenMP Tools Interface (OMPT). This option is supported and ON by default for x86, x86_64, AArch64, and PPC64 on Linux* and macOS*. This option is OFF if this feature is not supported for the platform.
LIBOMP_OMPT_OPTIONAL = ON|OFF
Include support for optional OMPT functionality. This option is ignored if LIBOMP_OMPT_SUPPORT is OFF.
LIBOMP_STATS = OFF|ON
Include stats-gathering code.
LIBOMP_USE_DEBUGGER = OFF|ON
Include the friendly debugger interface.
LIBOMP_USE_HWLOC = OFF|ON
Use OpenMPI's hwloc library for topology detection and affinity.
LIBOMP_HWLOC_INSTALL_DIR = /path/to/hwloc/install/dir
Specify install location of hwloc. The configuration system will look for hwloc.h in ${LIBOMP_HWLOC_INSTALL_DIR}/include and the library in ${LIBOMP_HWLOC_INSTALL_DIR}/lib. The default is /usr/local. This option is only used if LIBOMP_USE_HWLOC is ON.

These flags are appended, they do not overwrite any of the preset flags.

LIBOMP_CPPFLAGS = <space-separated flags>
Additional C preprocessor flags.
LIBOMP_CFLAGS = <space-separated flags>
Additional C compiler flags.
LIBOMP_CXXFLAGS = <space-separated flags>
Additional C++ compiler flags.
LIBOMP_ASMFLAGS = <space-separated flags>
Additional assembler flags.
LIBOMP_LDFLAGS = <space-separated flags>
Additional linker flags.
LIBOMP_LIBFLAGS = <space-separated flags>
Additional libraries to link.
LIBOMP_FFLAGS = <space-separated flags>
Additional Fortran compiler flags.
LIBOMPTARGET_OPENMP_HEADER_FOLDER = ""
Path of the folder that contains omp.h. This is required for testing out-of-tree builds.
LIBOMPTARGET_OPENMP_HOST_RTL_FOLDER = ""
Path of the folder that contains libomp.so. This is required for testing out-of-tree builds.
LIBOMPTARGET_NVPTX_ENABLE_BCLIB = ON|OFF
Enable CUDA LLVM bitcode offloading device RTL. This is used for link time optimization of the OMP runtime and application code. This option is enabled by default if the build system determines that CMAKE_C_COMPILER is able to compile and link the library.
LIBOMPTARGET_NVPTX_CUDA_COMPILER = ""
Location of a CUDA compiler capable of emitting LLVM bitcode. Currently only the Clang compiler is supported. This is only used when building the CUDA LLVM bitcode offloading device RTL. If unspecified and the CMake C compiler is Clang, then Clang is used.
LIBOMPTARGET_NVPTX_BC_LINKER = ""
Location of a linker capable of linking LLVM bitcode objects. This is only used when building the CUDA LLVM bitcode offloading device RTL. If unspecified and the CMake C compiler is Clang and there exists a llvm-link binary in the directory containing Clang, then this llvm-link binary is used.
LIBOMPTARGET_NVPTX_ALTERNATE_HOST_COMPILER = ""
Host compiler to use with NVCC. This compiler is not going to be used to produce any binary. Instead, this is used to overcome the input compiler checks done by NVCC. E.g. if using a default host compiler that is not compatible with NVCC, this option can be use to pass to NVCC a valid compiler to avoid the error.
LIBOMPTARGET_NVPTX_COMPUTE_CAPABILITIES = 35
List of CUDA compute capabilities that should be supported by the NVPTX device RTL. E.g. for compute capabilities 6.0 and 7.0, the option "60,70" should be used. Compute capability 3.5 is the minimum required.
LIBOMPTARGET_NVPTX_DEBUG = OFF|ON
Enable printing of debug messages from the NVPTX device RTL.
$ cmake -DCMAKE_C_COMPILER=clang -DCMAKE_CXX_COMPILER=clang++ ..
$ cmake -DCMAKE_C_COMPILER=gcc -DCMAKE_CXX_COMPILER=g++ ..
$ cmake -DCMAKE_C_COMPILER=icc -DCMAKE_CXX_COMPILER=icpc ..
  • Build the i386 Linux* library using GCC*

    $ cmake -DCMAKE_C_COMPILER=gcc -DCMAKE_CXX_COMPILER=g++ -DLIBOMP_ARCH=i386 ..
  • Build the x86_64 debug Mac library using Clang*

    $ cmake -DCMAKE_C_COMPILER=clang -DCMAKE_CXX_COMPILER=clang++ -DLIBOMP_ARCH=x86_64 -DCMAKE_BUILD_TYPE=Debug ..
  • Build the library (architecture determined by probing compiler) using the Intel(R) C Compiler and the Intel(R) C++ Compiler. Also, create Fortran modules with the Intel(R) Fortran Compiler.

    $ cmake -DCMAKE_C_COMPILER=icc -DCMAKE_CXX_COMPILER=icpc -DCMAKE_Fortran_COMPILER=ifort -DLIBOMP_FORTRAN_MODULES=on ..
  • Have CMake find the C/C++ compiler and specify additional flags for the C compiler, preprocessor, and C++ compiler.

    .. code-blocks:: console
    
      $ cmake -DLIBOMP_CFLAGS='-specific-flag' -DLIBOMP_CPPFLAGS='-DNEW_FEATURE=1 -DOLD_FEATURE=0' -DLIBOMP_CXXFLAGS='--one-specific-flag --two-specific-flag' ..
    
    
  • Build the stubs library

    .. code-blocks:: console
    
      $ cmake -DCMAKE_C_COMPILER=gcc -DCMAKE_CXX_COMPILER=g++ -DLIBOMP_LIB_TYPE=stubs ..
    
    

Footnotes

[*]Other names and brands may be claimed as the property of others.

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LB4OMP is an extended LLVM OpenMP runtime library that supports thirteen dynamic and adaptive loop scheduling techniques from the literature.

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