| Line | Branch | Exec | Source |
|---|---|---|---|
| 1 | #include "lobanov_d_multi_matrix_crs/omp/include/ops_omp.hpp" | ||
| 2 | |||
| 3 | #include <cmath> | ||
| 4 | #include <cstddef> | ||
| 5 | #include <map> | ||
| 6 | #include <vector> | ||
| 7 | |||
| 8 | #include "lobanov_d_multi_matrix_crs/common/include/common.hpp" | ||
| 9 | #include "util/include/util.hpp" | ||
| 10 | |||
| 11 | namespace lobanov_d_multi_matrix_crs { | ||
| 12 | |||
| 13 | ✗ | LobanovMultyMatrixOMP::LobanovMultyMatrixOMP(const InType &in) { | |
| 14 | SetTypeOfTask(GetStaticTypeOfTask()); | ||
| 15 | GetInput() = in; | ||
| 16 | ✗ | GetOutput() = CompressedRowMatrix{}; | |
| 17 | ✗ | } | |
| 18 | |||
| 19 | ✗ | bool LobanovMultyMatrixOMP::ValidationImpl() { | |
| 20 | const auto &matrix_a = GetInput().first; | ||
| 21 | const auto &matrix_b = GetInput().second; | ||
| 22 | |||
| 23 | ✗ | if (matrix_a.row_count <= 0 || matrix_b.row_count <= 0 || matrix_a.column_count <= 0 || matrix_b.column_count <= 0) { | |
| 24 | return false; | ||
| 25 | } | ||
| 26 | ✗ | if (matrix_a.column_count != matrix_b.row_count) { | |
| 27 | return false; | ||
| 28 | } | ||
| 29 | ✗ | if (matrix_a.row_pointer_data.size() != static_cast<size_t>(matrix_a.row_count) + 1 || | |
| 30 | ✗ | matrix_b.row_pointer_data.size() != static_cast<size_t>(matrix_b.row_count) + 1) { | |
| 31 | return false; | ||
| 32 | } | ||
| 33 | ✗ | if (static_cast<size_t>(matrix_a.non_zero_count) != matrix_a.value_data.size() || | |
| 34 | ✗ | static_cast<size_t>(matrix_a.non_zero_count) != matrix_a.column_index_data.size() || | |
| 35 | ✗ | static_cast<size_t>(matrix_b.non_zero_count) != matrix_b.value_data.size() || | |
| 36 | static_cast<size_t>(matrix_b.non_zero_count) != matrix_b.column_index_data.size()) { | ||
| 37 | ✗ | return false; | |
| 38 | } | ||
| 39 | return true; | ||
| 40 | } | ||
| 41 | |||
| 42 | ✗ | bool LobanovMultyMatrixOMP::PreProcessingImpl() { | |
| 43 | const auto &matrix_a = GetInput().first; | ||
| 44 | const auto &matrix_b = GetInput().second; | ||
| 45 | |||
| 46 | auto &result = GetOutput(); | ||
| 47 | ✗ | result.row_count = matrix_a.row_count; | |
| 48 | ✗ | result.column_count = matrix_b.column_count; | |
| 49 | ✗ | result.non_zero_count = 0; | |
| 50 | result.value_data.clear(); | ||
| 51 | result.column_index_data.clear(); | ||
| 52 | ✗ | result.row_pointer_data.assign(static_cast<size_t>(result.row_count) + 1, 0); | |
| 53 | ✗ | return true; | |
| 54 | } | ||
| 55 | |||
| 56 | ✗ | bool LobanovMultyMatrixOMP::RunImpl() { | |
| 57 | ✗ | const auto &matrix_a = GetInput().first; | |
| 58 | ✗ | const auto &matrix_b = GetInput().second; | |
| 59 | auto &result = GetOutput(); | ||
| 60 | |||
| 61 | ✗ | const int rows_a = matrix_a.row_count; | |
| 62 | |||
| 63 | ✗ | std::vector<std::map<int, double>> row_results(static_cast<size_t>(rows_a)); | |
| 64 | |||
| 65 | ✗ | #pragma omp parallel for default(none) shared(matrix_a, matrix_b, row_results, rows_a) \ | |
| 66 | ✗ | num_threads(ppc::util::GetNumThreads()) schedule(dynamic) | |
| 67 | for (int i = 0; i < rows_a; ++i) { | ||
| 68 | const int a_start = matrix_a.row_pointer_data[static_cast<size_t>(i)]; | ||
| 69 | const int a_end = matrix_a.row_pointer_data[static_cast<size_t>(i) + 1]; | ||
| 70 | |||
| 71 | for (int a_idx = a_start; a_idx < a_end; ++a_idx) { | ||
| 72 | const int k = matrix_a.column_index_data[static_cast<size_t>(a_idx)]; | ||
| 73 | const double a_val = matrix_a.value_data[static_cast<size_t>(a_idx)]; | ||
| 74 | |||
| 75 | if (k >= matrix_b.row_count) { | ||
| 76 | continue; | ||
| 77 | } | ||
| 78 | |||
| 79 | const int b_start = matrix_b.row_pointer_data[static_cast<size_t>(k)]; | ||
| 80 | const int b_end = matrix_b.row_pointer_data[static_cast<size_t>(k) + 1]; | ||
| 81 | |||
| 82 | for (int b_idx = b_start; b_idx < b_end; ++b_idx) { | ||
| 83 | const int j = matrix_b.column_index_data[static_cast<size_t>(b_idx)]; | ||
| 84 | const double b_val = matrix_b.value_data[static_cast<size_t>(b_idx)]; | ||
| 85 | |||
| 86 | row_results[static_cast<size_t>(i)][j] += a_val * b_val; | ||
| 87 | } | ||
| 88 | } | ||
| 89 | } | ||
| 90 | |||
| 91 | int offset = 0; | ||
| 92 | ✗ | result.row_pointer_data[0] = 0; | |
| 93 | ✗ | for (int i = 0; i < rows_a; ++i) { | |
| 94 | ✗ | const auto &row = row_results[static_cast<size_t>(i)]; | |
| 95 | ✗ | for (const auto &[col, val] : row) { | |
| 96 | ✗ | if (std::abs(val) > 1e-12) { | |
| 97 | ✗ | result.column_index_data.push_back(col); | |
| 98 | ✗ | result.value_data.push_back(val); | |
| 99 | ✗ | ++offset; | |
| 100 | } | ||
| 101 | } | ||
| 102 | ✗ | result.row_pointer_data[static_cast<size_t>(i) + 1] = offset; | |
| 103 | } | ||
| 104 | ✗ | result.non_zero_count = static_cast<int>(result.value_data.size()); | |
| 105 | |||
| 106 | ✗ | return true; | |
| 107 | ✗ | } | |
| 108 | |||
| 109 | ✗ | bool LobanovMultyMatrixOMP::PostProcessingImpl() { | |
| 110 | ✗ | return true; | |
| 111 | } | ||
| 112 | |||
| 113 | } // namespace lobanov_d_multi_matrix_crs | ||
| 114 |