Skip to content

v0.5.0
Compare
Choose a tag to compare
@davidbeckingsale davidbeckingsale released this 11 Jan 19:19
v0.5.0
9b539d8
This commit was created on GitHub.com and signed with GitHub’s verified signature. The key has expired.
GPG key ID: 4AEE18F83AFDEB23
Expired
Verified
Learn about vigilant mode.

Please download the RAJA-0.5.0.tar.gz file above. The others will not work due to the way RAJA uses git submodules.

This release contains a variety of bug fixes, removes nvcc compiler
warnings, addition of unit tests to expand coverage, and a variety of
other code cleanup and improvements. The most notable changes in this
version include:

  • New RAJA User Guide and Tutorial along with a set of example codes
    that illustrate basic usage of RAJA features and which accompany
    the tutorial. The examples are in the RAJA/examples directory.
    The user guide is available online here:
    RAJA User Guide and Tutorial.

  • RAJA::IndexSet is now deprecated. You may still use it until it is
    removed in a future release -- you will see a notification message at
    compile time that it is deprecated.

    Index set functionality will now be available via RAJA::TypedIndexSet
    where you specify all segment types as template parameters when you
    declare an instance of it. This change allows us to: remove all virtual
    methods from the index set, be able to use index set objects to CUDA
    GPU kernels and all of their functionality, and support any arbitrary
    segment type even user-defined. Please see User Guide for details.

    Segment dependencies are being developed for the typed index set and
    will be available in a future release.

  • RAJA::nested::forall changes:

    • Addition of CUDA and OpenMP collapse policies for nested loops.
      OpenMP collapse will do what the OpenMP collapse clause does.
      CUDA collapse will collapse a loop nest into a single CUDA kernel based
      on how nested policies specify how the loop levels should be distributed
      over blocks and threads.

    • Added new policy RAJA::cuda_loop_exec to enable inner loops to run
      sequentially inside a CUDA kernel with RAJA::nested::forall.

    • Fixed RAJA::nested::forall so it now works with RAJA's CUDA Reducer
      types.

    • Removed TypedFor policies. For type safety of nested loop iteration
      variables, it makes more sense to use TypedRangeSegment since the
      variables are associated with the loop kernel and not the execution
      policy, which may be applied to multiple loops with different variables.

  • Fixed OpenMP scans to calculate chunks of work based on actual number of
    threads the OpenMP runtime makes available.

  • Enhancements and fixes to RAJA/CHAI interoperability.

  • Added aliases for several camp types in the RAJA namespace; e.g.,
    camp::make_tuple can now be accessed as RAJA::make_tuple. This
    change makes the RAJA API more consistent and clear.

Assets 3
Loading