Cuda11 support #603
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Cuda11 support #603
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upsj
reviewed
Jul 30, 2020
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## develop #603 +/- ##
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Coverage ? 93.01%
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Files ? 296
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Hits ? 19216
Misses ? 1444
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upsj
requested changes
Aug 7, 2020
upsj
approved these changes
Aug 10, 2020
Additionally, this commit * templatizes the create_* functions to avoid the need for cuda_data_type everywhere * fixes some issues with cusparse_bindings.hpp compiled in C++ code
cuSPARSE Generic can only do C = a*A*B, not C=a*A*B + b*C (this was confirmed by NVIDIA in a documentation bug report)
* otherwise, windows cmake still gives CMP0104 warning * generic api is available from cuda10.1 (expect for win), cuda11 (all)
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I also add the comments on #if condition
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#endif // condition |
yhmtsai
commented
Aug 10, 2020
Comment on lines
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to
+1056
| trans->get_col_idxs(), trans->get_row_ptrs(), copyValues, idxBase); | ||
| trans->get_row_ptrs(), trans->get_col_idxs(), copyValues, idxBase); |
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I also change the ordering here
* add #endif comment if #else/#elif is not in block * use size_type Co-authored-by: Terry Cojean <terry.cojean@kit.edu> Co-authored-by: Tobias Ribizel <ribizel@kit.edu> Co-authored-by: Thomas Grützmacher <thomas.gruetzmacher@kit.edu>
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Kudos, SonarCloud Quality Gate passed!
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tcojean
added a commit
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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
added a commit
that referenced
this pull request
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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this PR add cuda11 support.
Summary:
tiled_partitionFixes #613