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Test spmv transpose (Fix #829) #831

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merged 2 commits into from
Oct 14, 2020
Merged

Test spmv transpose (Fix #829) #831

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627183c
Test all 4 modes for spmv/spmv_mv
brian-kelley Oct 13, 2020
24c7634
Remove unused var
brian-kelley Oct 13, 2020
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90 changes: 66 additions & 24 deletions unit_test/sparse/Test_Sparse_spmv.hpp
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Original file line number Diff line number Diff line change
Expand Up @@ -51,7 +51,8 @@ struct fSPMV {
template <typename crsMat_t, typename x_vector_type, typename y_vector_type>
void sequential_spmv(crsMat_t input_mat, x_vector_type x, y_vector_type y,
typename y_vector_type::non_const_value_type alpha,
typename y_vector_type::non_const_value_type beta){
typename y_vector_type::non_const_value_type beta,
char mode = 'N'){

using graph_t = typename crsMat_t::StaticCrsGraphType;
using size_type_view_t = typename graph_t::row_map_type;
Expand All @@ -61,7 +62,9 @@ void sequential_spmv(crsMat_t input_mat, x_vector_type x, y_vector_type y,
using size_type = typename size_type_view_t::non_const_value_type;
using lno_t = typename lno_view_t::non_const_value_type;
using scalar_t = typename scalar_view_t::non_const_value_type;
using KAT = Kokkos::ArithTraits<scalar_t>;

mode = toupper(mode);

typename scalar_view_t::HostMirror h_values = Kokkos::create_mirror_view(input_mat.values);
Kokkos::deep_copy(h_values,input_mat.values);
Expand All @@ -84,15 +87,24 @@ void sequential_spmv(crsMat_t input_mat, x_vector_type x, y_vector_type y,

lno_t nr = input_mat.numRows();

for (lno_t i = 0; i < nr; ++i){
scalar_t result = 0;
for (size_type j = h_rowmap(i); j < h_rowmap(i+1); ++j){
//first, scale y by beta
for(size_t i = 0; i < h_y.extent(0); i++)
h_y(i) *= beta;

//then go through the matrix and accumulate the matrix-vector product
for (lno_t row = 0; row < nr; ++row) {
for (size_type j = h_rowmap(row); j < h_rowmap(row+1); ++j) {
lno_t col = h_entries(j);
scalar_t val = h_values(j);
scalar_t vector_val = h_x(col);
result += val * vector_val;
if(mode == 'N')
h_y(row) += alpha * val * h_x(col);
else if(mode == 'C')
h_y(row) += alpha * KAT::conj(val) * h_x(col);
else if(mode == 'T')
h_y(col) += alpha * val * h_x(row);
else if(mode == 'H')
h_y(col) += alpha * KAT::conj(val) * h_x(row);
}
h_y(i) = beta * h_y(i) + alpha * result;
}
KokkosKernels::Impl::safe_host_to_device_deep_copy (y.extent(0), h_y, y);
Kokkos::fence();
Expand All @@ -102,7 +114,7 @@ void sequential_spmv(crsMat_t input_mat, x_vector_type x, y_vector_type y,
template <typename crsMat_t, typename x_vector_type, typename y_vector_type>
void check_spmv(crsMat_t input_mat, x_vector_type x, y_vector_type y,
typename y_vector_type::non_const_value_type alpha,
typename y_vector_type::non_const_value_type beta) {
typename y_vector_type::non_const_value_type beta, char mode) {
//typedef typename crsMat_t::StaticCrsGraphType graph_t;
using ExecSpace = typename crsMat_t::execution_space;
using my_exec_space = Kokkos::RangePolicy<ExecSpace>;
Expand All @@ -114,14 +126,14 @@ void check_spmv(crsMat_t input_mat, x_vector_type x, y_vector_type y,
// so let us use y_value_type to determine
// the appropriate tolerance precision.
const y_value_mag_type eps = std::is_same<y_value_mag_type, float>::value ? 2*1e-3 : 1e-7;
const size_t nr = input_mat.numRows();
y_vector_type expected_y("expected", nr);
bool transposed = (mode == 'T') || (mode == 'H');
y_vector_type expected_y("expected", transposed ? input_mat.numCols() : input_mat.numRows());
Kokkos::deep_copy(expected_y, y);
Kokkos::fence();

sequential_spmv(input_mat, x, expected_y, alpha, beta);
sequential_spmv(input_mat, x, expected_y, alpha, beta, mode);
//KokkosKernels::Impl::print_1Dview(expected_y);
KokkosSparse::spmv("N", alpha, input_mat, x, beta, y);
KokkosSparse::spmv(&mode, alpha, input_mat, x, beta, y);
//KokkosKernels::Impl::print_1Dview(y);
int num_errors = 0;
Kokkos::parallel_reduce("KokkosSparse::Test::spmv",
Expand All @@ -137,7 +149,7 @@ void check_spmv(crsMat_t input_mat, x_vector_type x, y_vector_type y,
template <typename crsMat_t, typename x_vector_type, typename y_vector_type>
void check_spmv_mv(crsMat_t input_mat, x_vector_type x, y_vector_type y, y_vector_type expected_y,
typename y_vector_type::non_const_value_type alpha,
typename y_vector_type::non_const_value_type beta, int numMV) {
typename y_vector_type::non_const_value_type beta, int numMV, char mode) {
using ExecSpace = typename crsMat_t::execution_space;
using my_exec_space = Kokkos::RangePolicy<ExecSpace>;
using y_value_type = typename y_vector_type::non_const_value_type;
Expand All @@ -153,7 +165,7 @@ void check_spmv_mv(crsMat_t input_mat, x_vector_type x, y_vector_type y, y_vecto

Kokkos::fence();

KokkosSparse::spmv("N", alpha, input_mat, x, beta, y);
KokkosSparse::spmv(&mode, alpha, input_mat, x, beta, y);


for (int i = 0; i < numMV; ++i){
Expand All @@ -162,7 +174,7 @@ void check_spmv_mv(crsMat_t input_mat, x_vector_type x, y_vector_type y, y_vecto
auto y_i = Kokkos::subview (expected_y, Kokkos::ALL (), i);
Kokkos::fence();

sequential_spmv(input_mat, x_i, y_i, alpha, beta);
sequential_spmv(input_mat, x_i, y_i, alpha, beta, mode);

auto y_spmv = Kokkos::subview (y, Kokkos::ALL (), i);
int num_errors = 0;
Expand Down Expand Up @@ -326,6 +338,8 @@ void test_spmv(lno_t numRows,size_type nnz, lno_t bandwidth, lno_t row_size_vari

x_vector_type input_x ("x", nc);
y_vector_type output_y ("y", nr);
x_vector_type input_xt ("x", nr);
y_vector_type output_yt ("y", nc);

Kokkos::Random_XorShift64_Pool<typename Device::execution_space> rand_pool(13718);

Expand All @@ -334,10 +348,23 @@ void test_spmv(lno_t numRows,size_type nnz, lno_t bandwidth, lno_t row_size_vari

Kokkos::fill_random(input_x,rand_pool,ScalarX(10));
Kokkos::fill_random(output_y,rand_pool,ScalarY(10));
Kokkos::fill_random(input_xt,rand_pool,ScalarX(10));
Kokkos::fill_random(output_yt,rand_pool,ScalarY(10));

Test::check_spmv(input_mat, input_x, output_y, 1.0, 0.0);
Test::check_spmv(input_mat, input_x, output_y, 0.0, 1.0);
Test::check_spmv(input_mat, input_x, output_y, 1.0, 1.0);
std::vector<char> nonTransModes = {'N', 'C'};
std::vector<char> transModes = {'T', 'H'};
for(auto mode : nonTransModes)
{
Test::check_spmv(input_mat, input_x, output_y, 1.0, 0.0, mode);
Test::check_spmv(input_mat, input_x, output_y, 0.0, 1.0, mode);
Test::check_spmv(input_mat, input_x, output_y, 1.0, 1.0, mode);
}
for(auto mode : transModes)
{
Test::check_spmv(input_mat, input_xt, output_yt, 1.0, 0.0, mode);
Test::check_spmv(input_mat, input_xt, output_yt, 0.0, 1.0, mode);
Test::check_spmv(input_mat, input_xt, output_yt, 1.0, 1.0, mode);
}
}

template <typename scalar_t, typename lno_t, typename size_type, typename layout, class Device>
Expand All @@ -353,21 +380,36 @@ void test_spmv_mv(lno_t numRows,size_type nnz, lno_t bandwidth, lno_t row_size_v
ViewTypeY b_y("B",numCols,numMV);
ViewTypeY b_y_copy("B",numCols,numMV);

ViewTypeX b_xt("A",numCols,numMV);
ViewTypeY b_yt("B",numRows,numMV);
ViewTypeY b_yt_copy("B",numRows,numMV);

Kokkos::Random_XorShift64_Pool<typename Device::execution_space> rand_pool(13718);
Kokkos::fill_random(b_x,rand_pool,scalar_t(10));
Kokkos::fill_random(b_y,rand_pool,scalar_t(10));
Kokkos::fill_random(b_xt,rand_pool,scalar_t(10));
Kokkos::fill_random(b_yt,rand_pool,scalar_t(10));


crsMat_t input_mat = KokkosKernels::Impl::kk_generate_sparse_matrix<crsMat_t>(numRows,numCols,nnz,row_size_variance, bandwidth);

Kokkos::deep_copy(b_y_copy, b_y);
Kokkos::deep_copy(b_yt_copy, b_yt);


Test::check_spmv_mv(input_mat, b_x, b_y, b_y_copy, 1.0, 0.0, numMV);
Test::check_spmv_mv(input_mat, b_x, b_y, b_y_copy, 0.0, 1.0, numMV);
Test::check_spmv_mv(input_mat, b_x, b_y, b_y_copy, 1.0, 1.0, numMV);


std::vector<char> nonTransModes = {'N', 'C'};
std::vector<char> transModes = {'T', 'H'};
for(auto mode : nonTransModes)
{
Test::check_spmv_mv(input_mat, b_x, b_y, b_y_copy, 1.0, 0.0, numMV, mode);
Test::check_spmv_mv(input_mat, b_x, b_y, b_y_copy, 0.0, 1.0, numMV, mode);
Test::check_spmv_mv(input_mat, b_x, b_y, b_y_copy, 1.0, 1.0, numMV, mode);
}
for(auto mode : transModes)
{
Test::check_spmv_mv(input_mat, b_xt, b_yt, b_yt_copy, 1.0, 0.0, numMV, mode);
Test::check_spmv_mv(input_mat, b_xt, b_yt, b_yt_copy, 0.0, 1.0, numMV, mode);
Test::check_spmv_mv(input_mat, b_xt, b_yt, b_yt_copy, 1.0, 1.0, numMV, mode);
}
}

template <typename scalar_t, typename lno_t, typename size_type, class Device>
Expand Down