Fix the CAS with HIP and NVIDIA backends. #585
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On a similar note, here is the spack package update for Ginkgo: |
upsj
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pratikvn
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Codecov Report
@@ Coverage Diff @@
## develop #585 +/- ##
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Coverage 84.22% 84.22%
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Files 296 296
Lines 20655 20655
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Hits 17397 17397
Misses 3258 3258 Continue to review full report at Codecov.
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tcojean
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Aug 26, 2020
Release 1.3.0 of Ginkgo. The Ginkgo team is proud to announce the new minor release of Ginkgo version 1.3.0. This release brings CUDA 11 support, changes the default C++ standard to be C++14 instead of C++11, adds a new Diagonal matrix format and capacity for diagonal extraction, significantly improves the CMake configuration output format, adds the Ginkgo paper which got accepted into the Journal of Open Source Software (JOSS), and fixes multiple issues. Supported systems and requirements: + For all platforms, cmake 3.9+ + Linux and MacOS + gcc: 5.3+, 6.3+, 7.3+, all versions after 8.1+ + clang: 3.9+ + Intel compiler: 2017+ + Apple LLVM: 8.0+ + CUDA module: CUDA 9.0+ + HIP module: ROCm 2.8+ + Windows + MinGW and Cygwin: gcc 5.3+, 6.3+, 7.3+, all versions after 8.1+ + Microsoft Visual Studio: VS 2017 15.7+ + CUDA module: CUDA 9.0+, Microsoft Visual Studio + OpenMP module: MinGW or Cygwin. The current known issues can be found in the [known issues page](https://github.com/ginkgo-project/ginkgo/wiki/Known-Issues). Additions: + Add paper for Journal of Open Source Software (JOSS). [#479](#479) + Add a DiagonalExtractable interface. [#563](#563) + Add a new diagonal Matrix Format. [#580](#580) + Add Cuda11 support. [#603](#603) + Add information output after CMake configuration. [#610](#610) + Add a new preconditioner export example. [#595](#595) + Add a new cuda-memcheck CI job. [#592](#592) Changes: + Use unified memory in CUDA debug builds. [#621](#621) + Improve `BENCHMARKING.md` with more detailed info. [#619](#619) + Use C++14 standard instead of C++11. [#611](#611) + Update the Ampere sm information and CudaArchitectureSelector. [#588](#588) Fixes: + Fix documentation warnings and errors. [#624](#624) + Fix warnings for diagonal matrix format. [#622](#622) + Fix criterion factory parameters in CUDA. [#586](#586) + Fix the norm-type in the examples. [#612](#612) + Fix the WAW race in OpenMP is_sorted_by_column_index. [#617](#617) + Fix the example's exec_map by creating the executor only if requested. [#602](#602) + Fix some CMake warnings. [#614](#614) + Fix Windows building documentation. [#601](#601) + Warn when CXX and CUDA host compiler do not match. [#607](#607) + Fix reduce_add, prefix_sum, and doc-build. [#593](#593) + Fix find_library(cublas) issue on machines installing multiple cuda. [#591](#591) + Fix allocator in sellp read. [#589](#589) + Fix the CAS with HIP and NVIDIA backends. [#585](#585) Deletions: + Remove unused preconditioner parameter in LowerTrs. [#587](#587) Related PR: #625
tcojean
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Aug 27, 2020
The Ginkgo team is proud to announce the new minor release of Ginkgo version 1.3.0. This release brings CUDA 11 support, changes the default C++ standard to be C++14 instead of C++11, adds a new Diagonal matrix format and capacity for diagonal extraction, significantly improves the CMake configuration output format, adds the Ginkgo paper which got accepted into the Journal of Open Source Software (JOSS), and fixes multiple issues. Supported systems and requirements: + For all platforms, cmake 3.9+ + Linux and MacOS + gcc: 5.3+, 6.3+, 7.3+, all versions after 8.1+ + clang: 3.9+ + Intel compiler: 2017+ + Apple LLVM: 8.0+ + CUDA module: CUDA 9.0+ + HIP module: ROCm 2.8+ + Windows + MinGW and Cygwin: gcc 5.3+, 6.3+, 7.3+, all versions after 8.1+ + Microsoft Visual Studio: VS 2017 15.7+ + CUDA module: CUDA 9.0+, Microsoft Visual Studio + OpenMP module: MinGW or Cygwin. The current known issues can be found in the [known issues page](https://github.com/ginkgo-project/ginkgo/wiki/Known-Issues). Additions: + Add paper for Journal of Open Source Software (JOSS). [#479](#479) + Add a DiagonalExtractable interface. [#563](#563) + Add a new diagonal Matrix Format. [#580](#580) + Add Cuda11 support. [#603](#603) + Add information output after CMake configuration. [#610](#610) + Add a new preconditioner export example. [#595](#595) + Add a new cuda-memcheck CI job. [#592](#592) Changes: + Use unified memory in CUDA debug builds. [#621](#621) + Improve `BENCHMARKING.md` with more detailed info. [#619](#619) + Use C++14 standard instead of C++11. [#611](#611) + Update the Ampere sm information and CudaArchitectureSelector. [#588](#588) Fixes: + Fix documentation warnings and errors. [#624](#624) + Fix warnings for diagonal matrix format. [#622](#622) + Fix criterion factory parameters in CUDA. [#586](#586) + Fix the norm-type in the examples. [#612](#612) + Fix the WAW race in OpenMP is_sorted_by_column_index. [#617](#617) + Fix the example's exec_map by creating the executor only if requested. [#602](#602) + Fix some CMake warnings. [#614](#614) + Fix Windows building documentation. [#601](#601) + Warn when CXX and CUDA host compiler do not match. [#607](#607) + Fix reduce_add, prefix_sum, and doc-build. [#593](#593) + Fix find_library(cublas) issue on machines installing multiple cuda. [#591](#591) + Fix allocator in sellp read. [#589](#589) + Fix the CAS with HIP and NVIDIA backends. [#585](#585) Deletions: + Remove unused preconditioner parameter in LowerTrs. [#587](#587) Related PR: #627
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Also include the CAS third party tool when building only HIP with CUDA backend.
When creating the spack package for Ginkgo which support HIP, I found out that we have an issue with the CAS dependency when only building HIP on an NVIDIA machine. Indeed, the CAS in required in
hip/CMakeLists.txt, but inthird_party/CMakeLists.txtwe only include the CAS third party tool when building CUDA. This fixes that issue.Building Ginkgo on a CUDA platform with HIP works when also building the CUDA backend (this is the case by default since we automatically detect the CUDA installation). Only in spack this is set the CUDA backend to
OFFwhenever a dependency toCUDAis not explicitly stated.