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Unified tests #1117

Merged
merged 29 commits into from
Sep 29, 2022
Merged

Unified tests #1117

merged 29 commits into from
Sep 29, 2022

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upsj
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@upsj upsj commented Sep 12, 2022

This is a big one 😀 Most of our tests are 90% - 100% identical between different executors. In terms of maintenance, I don't think there is value in keeping them separate. If there is specific behavior we need to test, we can+

  • do that in an isolated executor-specific test
  • #ifdef the test away for other executors or
  • test it anyways, since more tests is more good (:

TODO:

  • Csr kernel tests

Depends on #1123
Closes #483

@upsj upsj added 1:ST:WIP This PR is a work in progress. Not ready for review. is:technical-debt This is aimed at reducing technical debt. labels Sep 12, 2022
@upsj upsj added this to the Ginkgo 1.5.0 milestone Sep 12, 2022
@upsj upsj self-assigned this Sep 12, 2022
@ginkgo-bot ginkgo-bot added mod:cuda This is related to the CUDA module. mod:dpcpp This is related to the DPC++ module. mod:hip This is related to the HIP module. mod:openmp This is related to the OpenMP module. reg:build This is related to the build system. reg:testing This is related to testing. type:factorization This is related to the Factorizations type:matrix-format This is related to the Matrix formats type:multigrid This is related to multigrid type:preconditioner This is related to the preconditioners type:solver This is related to the solvers type:stopping-criteria This is related to the stopping criteria labels Sep 12, 2022
@upsj upsj changed the base branch from develop to fallback_transpose September 16, 2022 17:52
@upsj upsj added 1:ST:ready-for-review This PR is ready for review and removed 1:ST:WIP This PR is a work in progress. Not ready for review. labels Sep 16, 2022
@upsj upsj marked this pull request as ready for review September 16, 2022 17:52
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upsj commented Sep 16, 2022

format!

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upsj commented Sep 17, 2022

format!

@upsj upsj force-pushed the unified_tests branch 2 times, most recently from 53759b2 to a02d707 Compare September 23, 2022 07:00
Co-authored-by: Yuhsiang M. Tsai <yhmtsai@gmail.com>
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Really nice work! A few comments and questions.

test/solver/cb_gmres_kernels.cpp Show resolved Hide resolved
test/preconditioner/jacobi_kernels.cpp Show resolved Hide resolved
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Thanks for tackling this!
It is a lot to go through so I'd suggest a few of us do it.

@@ -368,7 +368,7 @@ TYPED_TEST(ResidualNorm, SelfCalulatesAndWaitsTillResidualGoal)
ASSERT_EQ(stop_status.get_data()[0].has_converged(), false);
ASSERT_EQ(one_changed, false);

solution->at(0) = rhs_val - r<T>::value * T{0.9} * rhs_norm->at(0);
solution->at(0) = rhs_val - r<T>::value * T{0.5} * rhs_norm->at(0);
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Because 0.9 can't be exactly represented in single precision? 👍

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no, because I relaxed the complex error bounds to include a sqrt(2) factor

test/components/prefix_sum_kernels.cpp Outdated Show resolved Hide resolved
test/factorization/par_ilut_kernels.cpp Outdated Show resolved Hide resolved
test/matrix/dense_kernels.cpp Outdated Show resolved Hide resolved
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looks very good. I've left some smaller remarks. I guess we need to see if the coverage changes due to this.
I would also suggest getting more than 2 approvals, because a single person won't find all issues that might be hiding somewhere.

@@ -189,7 +189,8 @@ struct reduction_factor {
using nc_output = remove_complex<OutputType>;
using nc_precision = remove_complex<Precision>;
static constexpr nc_output value{
std::numeric_limits<nc_precision>::epsilon() * nc_output{10}};
std::numeric_limits<nc_precision>::epsilon() * nc_output{10} *
(gko::is_complex<Precision>() ? nc_output{1.4142} : one<nc_output>())};
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This is sqrt(2) right? So why not

Suggested change
(gko::is_complex<Precision>() ? nc_output{1.4142} : one<nc_output>())};
(gko::is_complex<Precision>() ? nc_output{std::sqrt(2f)} : one<nc_output>())};

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nice suggestion, thanks!

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unfortunately this doesn't work, because it needs to be constexpr

test/components/prefix_sum_kernels.cpp Outdated Show resolved Hide resolved
test/matrix/fbcsr_kernels.cpp Outdated Show resolved Hide resolved
test/matrix/csr_kernels2.cpp Outdated Show resolved Hide resolved
test/matrix/csr_kernels2.cpp Outdated Show resolved Hide resolved
test/components/absolute_array_kernels.cpp Outdated Show resolved Hide resolved
TEST_F(Csr, OneAutomaticalWorksWithDifferentMatrices)
{
auto automatical = std::make_shared<Mtx::automatical>(exec);
#ifdef GKO_COMPILING_CUDA
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nit:

Suggested change
#ifdef GKO_COMPILING_CUDA
#if defined(GKO_COMPILING_CUDA)

for uniformity

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We're not very consistent about this surprisingly, but most cases use #ifdef, not #if defined:

grep -rh "#if" test | sort | uniq -c
      2 #if !(GINKGO_COMMON_SINGLE_MODE)
     25 #if GINKGO_COMMON_SINGLE_MODE
      1 #if GKO_HAVE_PAPI_SDE
      3 #if HAS_REFERENCE
      2 #if defined(GKO_COMPILING_CUDA) || defined(GKO_COMPILING_HIP) || \
      1 #if defined(GKO_COMPILING_OMP) || defined(GKO_COMPILING_CUDA) || \
      1 #if defined(HAS_CUDA)
      1 #if defined(HAS_CUDA) || defined(HAS_HIP)
      2 #if defined(HAS_HIP) || defined(HAS_CUDA)
      6 #ifdef GINKGO_FAST_TESTS
      6 #ifdef GKO_COMPILING_CUDA
      1 #ifdef GKO_COMPILING_DPCPP
      6 #ifdef GKO_COMPILING_HIP
      4 #ifdef GKO_COMPILING_OMP
      2 #ifndef GKO_COMPILING_DPCPP
      2 #ifndef GKO_COMPILING_HIP
      1 #ifndef GKO_COMPILING_OMP
      1 #ifndef GKO_TEST_UTILS_EXECUTOR_HPP_

test/solver/idr_kernels.cpp Outdated Show resolved Hide resolved
test/solver/multigrid_kernels.cpp Outdated Show resolved Hide resolved
test/stop/criterion_kernels.cpp Outdated Show resolved Hide resolved
* remove unnecessary includes
* pull common type aliases into CommonTestFixture
* fix some test bounds

Co-authored-by: Marcel Koch <marcel.koch@kit.edu>
Co-authored-by: Fritz Göbel <fritz.goebel@kit.edu>
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the excess system in Isai uses true/false in different tests.
I am not in favor of that the init_executor uses overload by passing nullptr not template to choose which implementation.

test/matrix/csr_kernels2.cpp Show resolved Hide resolved
Comment on lines +512 to +513
GKO_ASSERT_MTX_EQ_SPARSITY(square_dmtx, square_mtx);
ASSERT_TRUE(square_dmtx->is_sorted_by_column_index());
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I do not looking into the eq sparsity.
maybe put the check of sorted_by_column before eq_sparsity in case eq_sparsity sorts the matrix?

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all the assertions take the matrix by const pointer, so this shouldn't be an issue

test/matrix/csr_kernels2.cpp Outdated Show resolved Hide resolved
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test/preconditioner/isai_kernels.cpp Outdated Show resolved Hide resolved
Comment on lines -294 to +282
GKO_ASSERT_MTX_NEAR(inverse, d_inverse, 10 * r<value_type>::value);
GKO_ASSERT_MTX_NEAR(inverse, d_inverse, 100 * r<value_type>::value);
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maybe need to be careful?

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I like to increase the error bounds with big margins to make sure we don't have any flaky tests if some compiler optimizations change the evaluation order. Do you think this is an issue here?

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I do not know actually.
Without knowing the testing problem, I can somehow accept 10 r as rounding issue. 100 r will be a little higher such that I start wondering whether there's something wrong or the wrong codes may also pass the test

Comment on lines +73 to +74
gko::stop::ResidualNorm<value_type>::build()
.with_reduction_factor(value_type{1e-15})
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still surprised at float germs can use 1e-15 as reduction_factor?

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1e-15 is representable as a normal float, are you talking about the unit roundoff here? But I think we always run into the Iteration stopping criterion anyways.

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yes, unit roundoff here. it's hard to reach that when in float.
I see, I miss the iteration criterion.

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LGTM!

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codecov bot commented Sep 28, 2022

Codecov Report

Base: 90.61% // Head: 90.06% // Decreases project coverage by -0.54% ⚠️

Coverage data is based on head (a8b7e69) compared to base (4c3320c).
Patch coverage: 100.00% of modified lines in pull request are covered.

❗ Current head a8b7e69 differs from pull request most recent head d0206b6. Consider uploading reports for the commit d0206b6 to get more accurate results

Additional details and impacted files
@@             Coverage Diff             @@
##           develop    #1117      +/-   ##
===========================================
- Coverage    90.61%   90.06%   -0.55%     
===========================================
  Files          508      508              
  Lines        44334    44327       -7     
===========================================
- Hits         40173    39925     -248     
- Misses        4161     4402     +241     
Impacted Files Coverage Δ
core/test/utils.hpp 100.00% <ø> (ø)
core/test/utils/fb_matrix_generator.hpp 88.70% <ø> (-1.62%) ⬇️
reference/test/matrix/csr_kernels.cpp 99.84% <ø> (+<0.01%) ⬆️
reference/test/stop/residual_norm_kernels.cpp 97.47% <ø> (ø)
test/base/device_matrix_data_kernels.cpp 100.00% <ø> (ø)
test/base/kernel_launch_generic.cpp 94.54% <ø> (-0.78%) ⬇️
test/components/absolute_array_kernels.cpp 100.00% <ø> (ø)
test/components/fill_array_kernels.cpp 100.00% <ø> (ø)
test/components/format_conversion_kernels.cpp 100.00% <ø> (ø)
test/components/precision_conversion_kernels.cpp 100.00% <ø> (ø)
... and 104 more

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LGTM!

Co-authored-by: Yuhsiang M. Tsai <yhmtsai@gmail.com>
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upsj commented Sep 29, 2022

format!

Co-authored-by: Tobias Ribizel <upsj@users.noreply.github.com>
@upsj upsj merged commit 409ff3a into develop Sep 29, 2022
@upsj upsj deleted the unified_tests branch September 29, 2022 12:31
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sonarcloud bot commented Sep 29, 2022

tcojean added a commit that referenced this pull request Nov 12, 2022
Advertise release 1.5.0 and last changes

+ Add changelog,
+ Update third party libraries
+ A small fix to a CMake file

See PR: #1195

The Ginkgo team is proud to announce the new Ginkgo minor release 1.5.0. This release brings many important new features such as:
- MPI-based multi-node support for all matrix formats and most solvers;
- full DPC++/SYCL support,
- functionality and interface for GPU-resident sparse direct solvers,
- an interface for wrapping solvers with scaling and reordering applied,
- a new algebraic Multigrid solver/preconditioner,
- improved mixed-precision support,
- support for device matrix assembly,

and much more.

If you face an issue, please first check our [known issues page](https://github.com/ginkgo-project/ginkgo/wiki/Known-Issues) and the [open issues list](https://github.com/ginkgo-project/ginkgo/issues) and if you do not find a solution, feel free to [open a new issue](https://github.com/ginkgo-project/ginkgo/issues/new/choose) or ask a question using the [github discussions](https://github.com/ginkgo-project/ginkgo/discussions).

Supported systems and requirements:
+ For all platforms, CMake 3.13+
+ C++14 compliant compiler
+ Linux and macOS
  + GCC: 5.5+
  + clang: 3.9+
  + Intel compiler: 2018+
  + Apple LLVM: 8.0+
  + NVHPC: 22.7+
  + Cray Compiler: 14.0.1+
  + CUDA module: CUDA 9.2+ or NVHPC 22.7+
  + HIP module: ROCm 4.0+
  + DPC++ module: Intel OneAPI 2021.3 with oneMKL and oneDPL. Set the CXX compiler to `dpcpp`.
+ Windows
  + MinGW and Cygwin: GCC 5.5+
  + Microsoft Visual Studio: VS 2019
  + CUDA module: CUDA 9.2+, Microsoft Visual Studio
  + OpenMP module: MinGW or Cygwin.


Algorithm and important feature additions:
+ Add MPI-based multi-node for all matrix formats and solvers (except GMRES and IDR). ([#676](#676), [#908](#908), [#909](#909), [#932](#932), [#951](#951), [#961](#961), [#971](#971), [#976](#976), [#985](#985), [#1007](#1007), [#1030](#1030), [#1054](#1054), [#1100](#1100), [#1148](#1148))
+ Porting the remaining algorithms (preconditioners like ISAI, Jacobi, Multigrid, ParILU(T) and ParIC(T)) to DPC++/SYCL, update to SYCL 2020, and improve support and performance ([#896](#896), [#924](#924), [#928](#928), [#929](#929), [#933](#933), [#943](#943), [#960](#960), [#1057](#1057), [#1110](#1110),  [#1142](#1142))
+ Add a Sparse Direct interface supporting GPU-resident numerical LU factorization, symbolic Cholesky factorization, improved triangular solvers, and more ([#957](#957), [#1058](#1058), [#1072](#1072), [#1082](#1082))
+ Add a ScaleReordered interface that can wrap solvers and automatically apply reorderings and scalings ([#1059](#1059))
+ Add a Multigrid solver and improve the aggregation based PGM coarsening scheme ([#542](#542), [#913](#913), [#980](#980), [#982](#982),  [#986](#986))
+ Add infrastructure for unified, lambda-based, backend agnostic, kernels and utilize it for some simple kernels ([#833](#833), [#910](#910), [#926](#926))
+ Merge different CUDA, HIP, DPC++ and OpenMP tests under a common interface ([#904](#904), [#973](#973), [#1044](#1044), [#1117](#1117))
+ Add a device_matrix_data type for device-side matrix assembly ([#886](#886), [#963](#963), [#965](#965))
+ Add support for mixed real/complex BLAS operations ([#864](#864))
+ Add a FFT LinOp for all but DPC++/SYCL ([#701](#701))
+ Add FBCSR support for NVIDIA and AMD GPUs and CPUs with OpenMP ([#775](#775))
+ Add CSR scaling ([#848](#848))
+ Add array::const_view and equivalent to create constant matrices from non-const data ([#890](#890))
+ Add a RowGatherer LinOp supporting mixed precision to gather dense matrix rows ([#901](#901))
+ Add mixed precision SparsityCsr SpMV support ([#970](#970))
+ Allow creating CSR submatrix including from (possibly discontinuous) index sets ([#885](#885), [#964](#964))
+ Add a scaled identity addition (M <- aI + bM) feature interface and impls for Csr and Dense ([#942](#942))


Deprecations and important changes:
+ Deprecate AmgxPgm in favor of the new Pgm name. ([#1149](#1149)).
+ Deprecate specialized residual norm classes in favor of a common `ResidualNorm` class ([#1101](#1101))
+ Deprecate CamelCase non-polymorphic types in favor of snake_case versions (like array, machine_topology, uninitialized_array, index_set) ([#1031](#1031), [#1052](#1052))
+ Bug fix: restrict gko::share to rvalue references (*possible interface break*) ([#1020](#1020))
+ Bug fix: when using cuSPARSE's triangular solvers, specifying the factory parameter `num_rhs` is now required when solving for more than one right-hand side, otherwise an exception is thrown ([#1184](#1184)).
+ Drop official support for old CUDA < 9.2 ([#887](#887))


Improved performance additions:
+ Reuse tmp storage in reductions in solvers and add a mutable workspace to all solvers ([#1013](#1013), [#1028](#1028))
+ Add HIP unsafe atomic option for AMD ([#1091](#1091))
+ Prefer vendor implementations for Dense dot, conj_dot and norm2 when available ([#967](#967)).
+ Tuned OpenMP SellP, COO, and ELL SpMV kernels for a small number of RHS ([#809](#809))


Fixes:
+ Fix various compilation warnings ([#1076](#1076), [#1183](#1183), [#1189](#1189))
+ Fix issues with hwloc-related tests ([#1074](#1074))
+ Fix include headers for GCC 12 ([#1071](#1071))
+ Fix for simple-solver-logging example ([#1066](#1066))
+ Fix for potential memory leak in Logger ([#1056](#1056))
+ Fix logging of mixin classes ([#1037](#1037))
+ Improve value semantics for LinOp types, like moved-from state in cross-executor copy/clones ([#753](#753))
+ Fix some matrix SpMV and conversion corner cases ([#905](#905), [#978](#978))
+ Fix uninitialized data ([#958](#958))
+ Fix CUDA version requirement for cusparseSpSM ([#953](#953))
+ Fix several issues within bash-script ([#1016](#1016))
+ Fixes for `NVHPC` compiler support ([#1194](#1194))


Other additions:
+ Simplify and properly name GMRES kernels ([#861](#861))
+ Improve pkg-config support for non-CMake libraries ([#923](#923), [#1109](#1109))
+ Improve gdb pretty printer ([#987](#987), [#1114](#1114))
+ Add a logger highlighting inefficient allocation and copy patterns ([#1035](#1035))
+ Improved and optimized test random matrix generation ([#954](#954), [#1032](#1032))
+ Better CSR strategy defaults ([#969](#969))
+ Add `move_from` to `PolymorphicObject` ([#997](#997))
+ Remove unnecessary device_guard usage ([#956](#956))
+ Improvements to the generic accessor for mixed-precision ([#727](#727))
+ Add a naive lower triangular solver implementation for CUDA ([#764](#764))
+ Add support for int64 indices from CUDA 11 onward with SpMV and SpGEMM ([#897](#897))
+ Add a L1 norm implementation ([#900](#900))
+ Add reduce_add for arrays ([#831](#831))
+ Add utility to simplify Dense View creation from an existing Dense vector ([#1136](#1136)).
+ Add a custom transpose implementation for Fbcsr and Csr transpose for unsupported vendor types ([#1123](#1123))
+ Make IDR random initilization deterministic ([#1116](#1116))
+ Move the algorithm choice for triangular solvers from Csr::strategy_type to a factory parameter ([#1088](#1088))
+ Update CUDA archCoresPerSM ([#1175](#1116))
+ Add kernels for Csr sparsity pattern lookup ([#994](#994))
+ Differentiate between structural and numerical zeros in Ell/Sellp ([#1027](#1027))
+ Add a binary IO format for matrix data ([#984](#984))
+ Add a tuple zip_iterator implementation ([#966](#966))
+ Simplify kernel stubs and declarations ([#888](#888))
+ Simplify GKO_REGISTER_OPERATION with lambdas ([#859](#859))
+ Simplify copy to device in tests and examples ([#863](#863))
+ More verbose output to array assertions ([#858](#858))
+ Allow parallel compilation for Jacobi kernels ([#871](#871))
+ Change clang-format pointer alignment to left ([#872](#872))
+ Various improvements and fixes to the benchmarking framework ([#750](#750), [#759](#759), [#870](#870), [#911](#911), [#1033](#1033), [#1137](#1137))
+ Various documentation improvements ([#892](#892), [#921](#921), [#950](#950), [#977](#977), [#1021](#1021), [#1068](#1068), [#1069](#1069), [#1080](#1080), [#1081](#1081), [#1108](#1108), [#1153](#1153), [#1154](#1154))
+ Various CI improvements ([#868](#868), [#874](#874), [#884](#884), [#889](#889), [#899](#899), [#903](#903),  [#922](#922), [#925](#925), [#930](#930), [#936](#936), [#937](#937), [#958](#958), [#882](#882), [#1011](#1011), [#1015](#1015), [#989](#989), [#1039](#1039), [#1042](#1042), [#1067](#1067), [#1073](#1073), [#1075](#1075), [#1083](#1083), [#1084](#1084), [#1085](#1085), [#1139](#1139), [#1178](#1178), [#1187](#1187))
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Unifying kernel tests
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