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Add an example to show how to debug performance with loggers. #360
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Codecov Report
@@ Coverage Diff @@
## develop #360 +/- ##
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+ Coverage 89.23% 90.02% +0.79%
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Files 286 136 -150
Lines 21882 6075 -15807
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- Hits 19526 5469 -14057
+ Misses 2356 606 -1750
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LGTM!
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It looks really good.
But I would prefer if you would mention the namespace gko::
for every lend
and clone
(and similar functions, but I think here, it was mostly these two).
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LGTM!
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The Ginkgo team is proud to announce the new minor release of Ginkgo version 1.1.0. This release brings several performance improvements, adds Windows support, adds support for factorizations inside Ginkgo and a new ILU preconditioner based on ParILU algorithm, among other things. For detailed information, check the respective issue. Supported systems and requirements: + For all platforms, cmake 3.9+ + Linux and MacOS + gcc: 5.3+, 6.3+, 7.3+, 8.1+ + clang: 3.9+ + Intel compiler: 2017+ + Apple LLVM: 8.0+ + CUDA module: CUDA 9.0+ + Windows + MinGW and CygWin: gcc 5.3+, 6.3+, 7.3+, 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: + Upper and lower triangular solvers ([#327](#327), [#336](#336), [#341](#341), [#342](#342)) + New factorization support in Ginkgo, and addition of the ParILU algorithm ([#305](#305), [#315](#315), [#319](#319), [#324](#324)) + New ILU preconditioner ([#348](#348), [#353](#353)) + Windows MinGW and Cygwin support ([#347](#347)) + Windows Visual studio support ([#351](#351)) + New example showing how to use ParILU as a preconditioner ([#358](#358)) + New example on using loggers for debugging ([#360](#360)) + Add two new 9pt and 27pt stencil examples ([#300](#300), [#306](#306)) + Allow benchmarking CuSPARSE spmv formats through Ginkgo's benchmarks ([#303](#303)) + New benchmark for sparse matrix format conversions ([#312](https://github.com/ginkgo-project/ginkgo/issues/312)[#317](https://github.com/ginkgo-project/ginkgo/issues/317)) + Add conversions between CSR and Hybrid formats ([#302](#302), [#310](#310)) + Support for sorting rows in the CSR format by column idices ([#322](#322)) + Addition of a CUDA COO SpMM kernel for improved performance ([#345](#345)) + Addition of a LinOp to handle perturbations of the form (identity + scalar * basis * projector) ([#334](#334)) + New sparsity matrix representation format with Reference and OpenMP kernels ([#349](#349), [#350](#350)) Fixes: + Accelerate GMRES solver for CUDA executor ([#363](#363)) + Fix BiCGSTAB solver convergence ([#359](#359)) + Fix CGS logging by reporting the residual for every sub iteration ([#328](#328)) + Fix CSR,Dense->Sellp conversion's memory access violation ([#295](#295)) + Accelerate CSR->Ell,Hybrid conversions on CUDA ([#313](#313), [#318](#318)) + Fixed slowdown of COO SpMV on OpenMP ([#340](#340)) + Fix gcc 6.4.0 internal compiler error ([#316](#316)) + Fix compilation issue on Apple clang++ 10 ([#322](#322)) + Make Ginkgo able to compile on Intel 2017 and above ([#337](#337)) + Make the benchmarks spmv/solver use the same matrix formats ([#366](#366)) + Fix self-written isfinite function ([#348](#348)) + Fix Jacobi issues shown by cuda-memcheck Tools and ecosystem: + Multiple improvements to the CI system and tools ([#296](#296), [#311](#311), [#365](#365)) + Multiple improvements to the Ginkgo containers ([#328](#328), [#361](#361)) + Add sonarqube analysis to Ginkgo ([#304](#304), [#308](#308), [#309](#309)) + Add clang-tidy and iwyu support to Ginkgo ([#298](#298)) + Improve Ginkgo's support of xSDK M12 policy by adding the `TPL_` arguments to CMake ([#300](#300)) + Add support for the xSDK R7 policy ([#325](#325)) + Fix examples in html documentation ([#367](#367))
The Ginkgo team is proud to announce the new minor release of Ginkgo version 1.1.0. This release brings several performance improvements, adds Windows support, adds support for factorizations inside Ginkgo and a new ILU preconditioner based on ParILU algorithm, among other things. For detailed information, check the respective issue. Supported systems and requirements: + For all platforms, cmake 3.9+ + Linux and MacOS + gcc: 5.3+, 6.3+, 7.3+, 8.1+ + clang: 3.9+ + Intel compiler: 2017+ + Apple LLVM: 8.0+ + CUDA module: CUDA 9.0+ + Windows + MinGW and Cygwin: gcc 5.3+, 6.3+, 7.3+, 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 + Upper and lower triangular solvers ([#327](#327), [#336](#336), [#341](#341), [#342](#342)) + New factorization support in Ginkgo, and addition of the ParILU algorithm ([#305](#305), [#315](#315), [#319](#319), [#324](#324)) + New ILU preconditioner ([#348](#348), [#353](#353)) + Windows MinGW and Cygwin support ([#347](#347)) + Windows Visual Studio support ([#351](#351)) + New example showing how to use ParILU as a preconditioner ([#358](#358)) + New example on using loggers for debugging ([#360](#360)) + Add two new 9pt and 27pt stencil examples ([#300](#300), [#306](#306)) + Allow benchmarking CuSPARSE spmv formats through Ginkgo's benchmarks ([#303](#303)) + New benchmark for sparse matrix format conversions ([#312](https://github.com/ginkgo-project/ginkgo/issues/312)[#317](https://github.com/ginkgo-project/ginkgo/issues/317)) + Add conversions between CSR and Hybrid formats ([#302](#302), [#310](#310)) + Support for sorting rows in the CSR format by column idices ([#322](#322)) + Addition of a CUDA COO SpMM kernel for improved performance ([#345](#345)) + Addition of a LinOp to handle perturbations of the form (identity + scalar * basis * projector) ([#334](#334)) + New sparsity matrix representation format with Reference and OpenMP kernels ([#349](#349), [#350](#350)) ### Fixes + Accelerate GMRES solver for CUDA executor ([#363](#363)) + Fix BiCGSTAB solver convergence ([#359](#359)) + Fix CGS logging by reporting the residual for every sub iteration ([#328](#328)) + Fix CSR,Dense->Sellp conversion's memory access violation ([#295](#295)) + Accelerate CSR->Ell,Hybrid conversions on CUDA ([#313](#313), [#318](#318)) + Fixed slowdown of COO SpMV on OpenMP ([#340](#340)) + Fix gcc 6.4.0 internal compiler error ([#316](#316)) + Fix compilation issue on Apple clang++ 10 ([#322](#322)) + Make Ginkgo able to compile on Intel 2017 and above ([#337](#337)) + Make the benchmarks spmv/solver use the same matrix formats ([#366](#366)) + Fix self-written isfinite function ([#348](#348)) + Fix Jacobi issues shown by cuda-memcheck ### Tools and ecosystem improvements + Multiple improvements to the CI system and tools ([#296](#296), [#311](#311), [#365](#365)) + Multiple improvements to the Ginkgo containers ([#328](#328), [#361](#361)) + Add sonarqube analysis to Ginkgo ([#304](#304), [#308](#308), [#309](#309)) + Add clang-tidy and iwyu support to Ginkgo ([#298](#298)) + Improve Ginkgo's support of xSDK M12 policy by adding the `TPL_` arguments to CMake ([#300](#300)) + Add support for the xSDK R7 policy ([#325](#325)) + Fix examples in html documentation ([#367](#367)) Related PR: #370
This PR adds an example mostly taken from the benchmarks to show how to use loggers to debug performance and residual convergence in Ginkgo.
The approach taken is to pass in as argument an optional file (and executor) which is the input matrix file in matrix market format.
In the code itself, at the beginning of the main functions, all important information for configuring the benchmark can be changed manually. The only other place the user may need to change is the preconditioner's settings when using a more complex one, in the solver factory declaration.
The benchmark has three segments:
Tell me if some other information should be shown.
Example of output (reference, simple example matrix):