unuse getrf in the getrs analytical test

kokkos · Jan 20, 2025 · 82ea131 · 82ea131
1 parent f99de7d
commit 82ea131
Showing 1 changed file with 24 additions and 22 deletions.
diff --git a/batched/dense/unit_test/Test_Batched_SerialGetrs.hpp b/batched/dense/unit_test/Test_Batched_SerialGetrs.hpp
@@ -33,7 +33,7 @@ struct ParamTag {
   using trans = T;
 };
 
-template <typename DeviceType, typename AViewType, typename PivViewType, typename AlgoTagType>
+template <typename DeviceType, typename AViewType, typename PivViewType>
 struct Functor_BatchedSerialGetrf {
   using execution_space = typename DeviceType::execution_space;
   AViewType m_a;
@@ -47,7 +47,7 @@ struct Functor_BatchedSerialGetrf {
     auto aa   = Kokkos::subview(m_a, k, Kokkos::ALL(), Kokkos::ALL());
     auto ipiv = Kokkos::subview(m_ipiv, k, Kokkos::ALL());
 
-    KokkosBatched::SerialGetrf<AlgoTagType>::invoke(aa, ipiv);
+    KokkosBatched::SerialGetrf<Algo::Getrf::Unblocked>::invoke(aa, ipiv);
   }
 
   inline void run() {
@@ -137,6 +137,10 @@ struct Functor_BatchedSerialGemv {
 /// This corresponds to the following system of equations:
 ///        x0 + x1 = 2
 ///        x0 - x1 = 0
+/// We confirm this with the factorized matrix LU and pivot given by
+///       LU: [[1, 1],
+///            [1, -2]]
+///       piv: [0, 1]
 ///
 /// \param N [in] Batch size of RHS (banded matrix can also be batched matrix)
 /// \param k [in] Number of superdiagonals or subdiagonals of matrix A
@@ -150,35 +154,33 @@ void impl_test_batched_getrs_analytical(const int N) {
   using PivView2DType = Kokkos::View<int **, LayoutType, DeviceType>;
 
   const int BlkSize = 2;
-  View3DType A("A", N, BlkSize, BlkSize), ref("Ref", N, BlkSize, BlkSize);
-  View3DType lu("lu", N, BlkSize, BlkSize);                                       // Factorized
-  View2DType x("x", N, BlkSize), y("y", N, BlkSize), x_ref("x_ref", N, BlkSize);  // Solutions
+  View3DType LU("LU", N, BlkSize, BlkSize);                   // Factorized matrix of A
+  View2DType x("x", N, BlkSize), x_ref("x_ref", N, BlkSize);  // Solutions
   PivView2DType ipiv("ipiv", N, BlkSize);
 
-  auto h_A     = Kokkos::create_mirror_view(A);
+  auto h_LU    = Kokkos::create_mirror_view(LU);
+  auto h_ipiv  = Kokkos::create_mirror_view(ipiv);
   auto h_x     = Kokkos::create_mirror_view(x);
   auto h_x_ref = Kokkos::create_mirror_view(x_ref);
-  Kokkos::deep_copy(h_A, 1.0);
+  Kokkos::deep_copy(h_LU, 1.0);
   for (int ib = 0; ib < N; ib++) {
-    h_A(ib, 1, 1) = -1.0;
+    h_LU(ib, 1, 1) = -2.0;
+    h_ipiv(ib, 0)  = 0;
+    h_ipiv(ib, 1)  = 1;
 
     h_x(ib, 0)     = 2;
     h_x(ib, 1)     = 0;
     h_x_ref(ib, 0) = 1;
     h_x_ref(ib, 1) = 1;
   }
 
-  Kokkos::fence();
-
-  Kokkos::deep_copy(A, h_A);
+  Kokkos::deep_copy(LU, h_LU);
+  Kokkos::deep_copy(ipiv, h_ipiv);
   Kokkos::deep_copy(x, h_x);
 
-  // getrf to factorize matrix A = P * L * U
-  Functor_BatchedSerialGetrf<DeviceType, View3DType, PivView2DType, AlgoTagType>(A, ipiv).run();
-
   // getrs (Note, LU is a factorized matrix of A)
   auto info = Functor_BatchedSerialGetrs<DeviceType, View3DType, PivView2DType, View2DType, ParamTagType, AlgoTagType>(
-                  A, ipiv, x)
+                  LU, ipiv, x)
                   .run();
 
   Kokkos::fence();
@@ -226,7 +228,7 @@ void impl_test_batched_getrs(const int N, const int BlkSize) {
   Kokkos::deep_copy(b, x);
 
   // getrf to factorize matrix A = P * L * U
-  Functor_BatchedSerialGetrf<DeviceType, View3DType, PivView2DType, AlgoTagType>(LU, ipiv).run();
+  Functor_BatchedSerialGetrf<DeviceType, View3DType, PivView2DType>(LU, ipiv).run();
 
   // getrs (Note, LU is a factorized matrix of A)
   auto info = Functor_BatchedSerialGetrs<DeviceType, View3DType, PivView2DType, View2DType, ParamTagType, AlgoTagType>(
@@ -317,19 +319,19 @@ TEST_F(TestCategory, test_batched_getrs_t_double) {
 #endif
 
 #if defined(KOKKOSKERNELS_INST_COMPLEX_FLOAT)
-TEST_F(TestCategory, test_batched_getrs_nt_cfloat) {
+TEST_F(TestCategory, test_batched_getrs_nt_fcomplex) {
   using param_tag_type = ::Test::Getrs::ParamTag<Trans::NoTranspose>;
   using algo_tag_type  = typename Algo::Getrs::Unblocked;
 
   test_batched_getrs<TestDevice, Kokkos::complex<float>, param_tag_type, algo_tag_type>();
 }
-TEST_F(TestCategory, test_batched_getrs_t_cfloat) {
+TEST_F(TestCategory, test_batched_getrs_t_fcomplex) {
   using param_tag_type = ::Test::Getrs::ParamTag<Trans::Transpose>;
   using algo_tag_type  = typename Algo::Getrs::Unblocked;
 
   test_batched_getrs<TestDevice, Kokkos::complex<float>, param_tag_type, algo_tag_type>();
 }
-TEST_F(TestCategory, test_batched_getrs_c_cfloat) {
+TEST_F(TestCategory, test_batched_getrs_c_fcomplex) {
   using param_tag_type = ::Test::Getrs::ParamTag<Trans::ConjTranspose>;
   using algo_tag_type  = typename Algo::Getrs::Unblocked;
 
@@ -338,19 +340,19 @@ TEST_F(TestCategory, test_batched_getrs_c_cfloat) {
 #endif
 
 #if defined(KOKKOSKERNELS_INST_COMPLEX_DOUBLE)
-TEST_F(TestCategory, test_batched_getrs_nt_dfloat) {
+TEST_F(TestCategory, test_batched_getrs_nt_dcomplex) {
   using param_tag_type = ::Test::Getrs::ParamTag<Trans::NoTranspose>;
   using algo_tag_type  = typename Algo::Getrs::Unblocked;
 
   test_batched_getrs<TestDevice, Kokkos::complex<double>, param_tag_type, algo_tag_type>();
 }
-TEST_F(TestCategory, test_batched_getrs_t_dfloat) {
+TEST_F(TestCategory, test_batched_getrs_t_dcomplex) {
   using param_tag_type = ::Test::Getrs::ParamTag<Trans::Transpose>;
   using algo_tag_type  = typename Algo::Getrs::Unblocked;
 
   test_batched_getrs<TestDevice, Kokkos::complex<double>, param_tag_type, algo_tag_type>();
 }
-TEST_F(TestCategory, test_batched_getrs_c_dfloat) {
+TEST_F(TestCategory, test_batched_getrs_c_dcomplex) {
   using param_tag_type = ::Test::Getrs::ParamTag<Trans::ConjTranspose>;
   using algo_tag_type  = typename Algo::Getrs::Unblocked;