replica
/
hanchenye-llvm-project
2
0
Fork 0
Code Issues Pull Requests Projects Releases Wiki Activity
hanchenye-llvm-project/pstl
History
Hans Wennborg eb60fbfdb4 Update year in license files 
In last year's update (D48219) it was suggested that the release manager
might want to do this, so here we go.

llvm-svn: 351194
 		2019-01-15 15:10:32 +00:00
..
build
…
cmake [pstl] Initial integration with LLVM's CMake 2018-12-21 15:59:04 +00:00
include/pstl [pstl] Fix compile errors when PARALLEL_POLICIES is disabled 2019-01-10 11:23:33 +00:00
test [pstl] Initial integration with LLVM's CMake 2018-12-21 15:59:04 +00:00
.arcconfig
…
.clang-format
…
CMakeLists.txt [pstl] Fix CMake configuration when parallel policies are disabled 2019-01-10 11:17:26 +00:00
CREDITS.txt
…
LICENSE.txt Update year in license files 2019-01-15 15:10:32 +00:00
ParallelSTLConfig.cmake.in
…
README.md [NFC] Fix formatting of README.md for better rendering 2019-01-07 16:54:02 +00:00

README.md

Parallel STL

Parallel STL is an implementation of the C++ standard library algorithms with support for execution policies, as specified in ISO/IEC 14882:2017 standard, commonly called C++17. The implementation also supports the unsequenced execution policy specified in Parallelism TS version 2 and proposed for the next version of the C++ standard in the C++ working group paper P1001. Parallel STL offers efficient support for both parallel and vectorized execution of algorithms. For sequential execution, it relies on an available implementation of the C++ standard library.

Prerequisites

To use Parallel STL, you must have the following software installed:

  • C++ compiler with:
    • Support for C++11
    • Support for OpenMP* 4.0 SIMD constructs
  • Threading Building Blocks (TBB) which is available for download at https://github.com/01org/tbb/

Known issues and limitations

  • unseq and par_unseq policies only have effect with compilers that support #pragma omp simd or #pragma simd.
  • Parallel and vector execution is only supported for the algorithms if random access iterators are provided, while for other iterator types the execution will remain serial.
  • The following algorithms do not allow efficient SIMD execution: includes, inplace_merge, merge, nth_element, partial_sort, partial_sort_copy, set_difference, set_intersection, set_symmetric_difference, set_union, sort, stable_partition, stable_sort, unique.
  • The initial value type for exclusive_scan, inclusive_scan, transform_exclusive_scan, transform_inclusive_scan shall be DefaultConstructible. A default constructed-instance of the initial value type shall be the identity element for the specified binary operation.
  • For max_element, min_element, minmax_element, partial_sort, partial_sort_copy, sort, stable_sort the dereferenced value type of the provided iterators shall be DefaultConstructible.
  • For remove, remove_if, unique the dereferenced value type of the provided iterators shall be MoveConstructible.
  • The following algorithms require additional O(n) memory space for parallel execution: copy_if, inplace_merge, partial_sort, partial_sort_copy, partition_copy, remove, remove_if, rotate, sort, stable_sort, unique, unique_copy.