Skip to content

Latest commit

 

History

History
127 lines (94 loc) · 5.4 KB

RELEASE_NOTES.md

File metadata and controls

127 lines (94 loc) · 5.4 KB
Raw

RAJA v0.6.0 Release Notes

This release contains two major changes, a variety of bug fixes and feature enhancements, and expanded user documentation and accompanying example codes.

Major changes include:

  • RAJA::forallN methods are marked deprecated. They will be removed in the 0.7.0 release.
  • RAJA::forall methods that take loop bounds rather than segments (e.g., RAJA::forall(beg, end, ...) are marked deprecated. They will be removed in the 0.7.0 release.
  • RAJA::nested has been replaced with RAJA::kernel. The RAJA::kernel interface is much more flexible and full featured. Going forward, it will be the supported interface for nested loops and more complex kernels in RAJA.
  • This release contains new documentation and example codes for the RAJA::kernel interface. The documentation described key features and summarizes available 'statement' types. However, it remains a work-in-progress and expanded documentation with more examples will be available in future releases.
  • Documentation of other RAJA features have been expanded and improved in this release along with additional example codes.

Other notable changes include:

  • New or improved features:

    • RAJA CUDA reductions now work with host/device lambdas
    • List segments now work with RAJA::kernel loops.
    • New and expanded collection of build files for LC and ALCF machines. Hopefully, these will be helpful to folks getting started.

  • Performance improvements:

    • Some RAJA::View use cases
    • Unnecessary operations removed in min/max atomics

  • Bug fixes:

    • Issues in View with OffsetLayout fixed.
    • Construction of a const View from a non-const View now works
    • CUDA kernel no longer launched in RAJA::kernel loops when iteration space has size zero

RAJA v0.5.3 Release Notes

This is a bugfix release that fixes bugs in the IndexSetBuilder methods. These methods now work correctly with the strongly-typed IndexSet.

RAJA v0.5.2 Release Notes

This release fixes some small bugs, including compiler warnings issued for deprecated features, type narrowing, and the slice method for the RangeStrideSegment class.

It also adds a new CMake variable, RAJA_LOADED, that is used to determine whether RAJA's CMakeLists file has already been processed. This is useful when including RAJA as part of another CMake project.

RAJA v0.5.1 Release Notes

This release contains fixes for compiler warnings with newer GCC and Clang compilers, and allows strongly-typed indices to work with RangeStrideSegment.

Additionally, the index type for all segments in an IndexSet needs to be the same. This requirement is enforced with a static_assert.

RAJA v0.5.0 Release Notes

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.