RAJA Performance Portability Layer (C++)
This release contains submodule updates and minor RAJA improvements.
Please download the RAJA-v2024.02.1.tar.gz file below. The others, generated by GitHub, may not work for you due to RAJA's dependencies on git submodules.
Notable changes include:
New features / API changes:
Build changes/improvements:
Bug fixes/improvements:
This release contains several RAJA improvements and submodule updates.
Please download the RAJA-v2024.02.0.tar.gz file below. The others, generated by GitHub, may not work for you due to RAJA's dependencies on git submodules.
Notable changes include:
New features / API changes:
loop_exec
and associated policies such as loop_atomic
, loop_reduce
, etc. were deprecated in the v2023.06.0 release (please see the release notes for that version for details). Users should replace these with seq_exec
and associated policies for sequential CPU execution. The code behavior will be identical to what you observed with loop_exec
, etc. However, due to a request from some users with special circumstances, the loop_*
policies still exist in this release as type aliases to their seq_*
analogues. The loop_*
policies will be removed in a future release.IndexLayout
concept was added, which allows for accessing elements of a RAJA View
via a collection of indicies and use a different indexing strategy along different dimensions of a multi-dimensional View
. Please the RAJA User Guide for more information.Build changes/improvements:
Bug fixes/improvements:
This release contains various smallish RAJA improvements.
Please download the RAJA-v2023.06.1.tar.gz file below. The others, generated by GitHub, may not work for you due to RAJA's dependencies on git submodules.
Notable changes include:
New features / API changes:
Build changes/improvements:
Bug fixes/improvements:
This release contains new features to improve GPU kernel performance and some bug fixes. It contains one breaking change described below and an execution policy deprecation also described below. The policy deprecation is not a breaking change in this release, but will result in a breaking change in the next release.
Please download the RAJA-v2023.06.0.tar.gz file below. The others, generated by GitHub, may not work for you due to RAJA's dependencies on git submodules.
Notable changes include:
New features / API changes:
Build changes/improvements:
Bug fixes/improvements:
This release fixes an issue that was found after the v2022.10.4 release.
Please download the RAJA-v2022.10.5.tar.gz file below. The others, generated by GitHub, may not work for you due to RAJA's dependencies on git submodules.
This release fixes a few issues that were found after the v2022.10.3 patch release and updates a few other things.
Please download the RAJA-v2022.10.4.tar.gz file below. The others, generated by GitHub, may not work for you due to RAJA's dependencies on git submodules.
Notable changes include:
This release fixes a few issues that were found after the v2022.10.3 patch release and updates a few other things.
Please download the RAJA-v2022.10.3.tar.gz file below. The others, generated by GitHub, may not work for you due to RAJA's dependencies on git submodules.
Notable changes include:
Update camp submodule to v2022.10.1
Update BLT submodule to commit 8c229991 (includes fixes for crayftn + hip)
Properly export 'roctx' target when CMake variable RAJA_ENABLE_ROCTX is on.
Fix CMake logic for exporting desul targets when desul atomics are enabled.
Fix the way we use CMake to find the rocPRIM module to follow CMake best practices.
Add missing template parameter pack argument in RAJA::statement::For execution policy construct used in RAJA::kernel implementation for OpenMP target back-end.
Change to use compile-time GPU thread block size in RAJA::forall implementation. This improves performance of GPU kernels, especially those using the RAJA HIP back-end.
Added RAJA plugin support, including CHAI support, for RAJA::launch.
Replaced 'DEVICE' macro with alias to 'device_mem_pool_t' to prevent name conflicts with other libraries.
Updated User Guide documentation about CMake variable used to pass compiler flags for OpenMP target back-end. This changed with CMake minimum required version bump in v2022.10.0.
Adjust ordering of BLT and camp target inclusion in RAJA CMake usage to fix an issue with projects using external camp vs. RAJA submodule.
This release fixes a few issues that were found after the v2022.10.1 patch release and updates a few things. Sorry for the churn, folks.
Please download the RAJA-v2022.10.2.tar.gz file below. The others, generated by GitHub, may not work for you due to RAJA's dependencies on git submodules.
Notable changes include:
Update desul submodule to commit e4b65e00.
CUDA compute architecture must now be set using the 'CMAKE_CUDA_ARCHITECTURES' CMake variable. For example, by passing '-DCMAKE_CUDA_ARCHITECTURES=70' to CMake for 'sm_70' architecture. Using '-DCUDA_ARCH=sm_*' will not no longer do the right thing. Please see the RAJA User Guide for more information.
A linking bug was fixed related to the usage of the new RAJA::KernelName capability.
A compilation bug was fixed in the new reduction interface support for OpenMP target offload.
An issue was fixed in AVX compiler checking logic for RAJA vectorization intrinsics capabilities.
This release updates the RAJA release number in CMake, which was inadvertently missed in the v2022.10.0 release.
Please download the RAJA-v2022.10.1.tar.gz file below. The others, generated by GitHub, may not work for you due to RAJA's dependencies on git submodules.
This release contains new features, bug fixes, and build improvements. Please see the RAJA user guide for more information about items in this release.
Please download the RAJA-v2022.10.0.tar.gz file below. The others, generated by GitHub, may not work for you due to RAJA's dependencies on git submodules.
Notable changes include:
New features / API changes:
Build changes / improvements:
Bug fixes / improvements: