Unified tests #1117

upsj · 2022-09-12T05:14:15Z

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 · 2022-09-16T17:53:53Z

format!

upsj · 2022-09-17T08:05:02Z

format!

Co-authored-by: Tobias Ribizel <[email protected]>

Co-authored-by: Yuhsiang M. Tsai <[email protected]>

pratikvn

Really nice work! A few comments and questions.

test/solver/cb_gmres_kernels.cpp

test/preconditioner/jacobi_kernels.cpp

test/matrix/csr_kernels2.cpp

fritzgoebel

Thanks for tackling this!
It is a lot to go through so I'd suggest a few of us do it.

fritzgoebel · 2022-09-19T08:00:10Z

reference/test/stop/residual_norm_kernels.cpp

@@ -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);


Because 0.9 can't be exactly represented in single precision? 👍

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

test/components/prefix_sum_kernels.cpp

test/factorization/par_ilut_kernels.cpp

test/matrix/dense_kernels.cpp

MarcelKoch

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.

MarcelKoch · 2022-09-23T09:22:49Z

core/test/utils.hpp

@@ -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>())};


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>())};

nice suggestion, thanks!

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

test/components/prefix_sum_kernels.cpp

test/matrix/fbcsr_kernels.cpp

test/matrix/csr_kernels2.cpp

test/components/absolute_array_kernels.cpp

MarcelKoch · 2022-09-23T09:55:38Z

test/matrix/csr_kernels2.cpp

+TEST_F(Csr, OneAutomaticalWorksWithDifferentMatrices)
+{
+    auto automatical = std::make_shared<Mtx::automatical>(exec);
+#ifdef GKO_COMPILING_CUDA


nit:

Suggested change

#ifdef GKO_COMPILING_CUDA

#if defined(GKO_COMPILING_CUDA)

for uniformity

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

test/solver/multigrid_kernels.cpp

test/stop/criterion_kernels.cpp

* remove unnecessary includes * pull common type aliases into CommonTestFixture * fix some test bounds Co-authored-by: Marcel Koch <[email protected]> Co-authored-by: Fritz Göbel <[email protected]>

yhmtsai

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

yhmtsai · 2022-09-28T14:52:52Z

test/matrix/csr_kernels2.cpp

+    GKO_ASSERT_MTX_EQ_SPARSITY(square_dmtx, square_mtx);
+    ASSERT_TRUE(square_dmtx->is_sorted_by_column_index());


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?

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

test/matrix/csr_kernels2.cpp

test/preconditioner/isai_kernels.cpp

yhmtsai · 2022-09-28T15:07:40Z

test/preconditioner/isai_kernels.cpp

-    GKO_ASSERT_MTX_NEAR(inverse, d_inverse, 10 * r<value_type>::value);
+    GKO_ASSERT_MTX_NEAR(inverse, d_inverse, 100 * r<value_type>::value);


maybe need to be careful?

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?

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

yhmtsai · 2022-09-28T15:20:11Z

test/solver/gmres_kernels.cpp

+                    gko::stop::ResidualNorm<value_type>::build()
+                        .with_reduction_factor(value_type{1e-15})


still surprised at float germs can use 1e-15 as reduction_factor?

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.

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

pratikvn

LGTM!

test/preconditioner/isai_kernels.cpp

codecov · 2022-09-28T16:19:57Z

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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fritzgoebel

LGTM!

Co-authored-by: Yuhsiang M. Tsai <[email protected]>

upsj · 2022-09-29T08:00:40Z

format!

Co-authored-by: Tobias Ribizel <[email protected]>

sonarqubecloud · 2022-09-29T15:20:48Z

SonarCloud Quality Gate failed.

0 Bugs
0 Vulnerabilities
0 Security Hotspots
1100 Code Smells

94.7% Coverage
8.3% Duplication

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))

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

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upsj and others added 6 commits September 23, 2022 07:41

fix FFT test compile guard

fe0a77b

improve jacobi test output

3e6e03c

Format files

60d8531

Co-authored-by: Tobias Ribizel <[email protected]>

fix GMRES kernels

2ba3f88

csr_kernels

8af2dc7

formatting and dpcpp fixes

ef2b32f

upsj force-pushed the unified_tests branch 2 times, most recently from 53759b2 to a02d707 Compare September 23, 2022 07:00

review updates and fixes

3dadd5c

Co-authored-by: Yuhsiang M. Tsai <[email protected]>

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MarcelKoch mentioned this pull request Sep 26, 2022

Adds distributed support for several solvers #976

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* remove unnecessary includes * pull common type aliases into CommonTestFixture * fix some test bounds Co-authored-by: Marcel Koch <[email protected]> Co-authored-by: Fritz Göbel <[email protected]>

upsj force-pushed the unified_tests branch from 6065162 to e8b73a2 Compare September 28, 2022 07:53

fix dpcpp tests, use type aliases consistently

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Unified tests #1117

Unified tests #1117

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

		GKO_ASSERT_MTX_EQ_SPARSITY(square_dmtx, square_mtx);
		ASSERT_TRUE(square_dmtx->is_sorted_by_column_index());

		GKO_ASSERT_MTX_NEAR(inverse, d_inverse, 10 * r<value_type>::value);
		GKO_ASSERT_MTX_NEAR(inverse, d_inverse, 100 * r<value_type>::value);

		gko::stop::ResidualNorm<value_type>::build()
		.with_reduction_factor(value_type{1e-15})

Unified tests #1117

Unified tests #1117

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