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|---|---|---|---|
| 1 | #include "vlasova_a_matrix_multiply_ccs/seq/include/ops_seq.hpp" | ||
| 2 | |||
| 3 | #include <cmath> | ||
| 4 | #include <cstddef> | ||
| 5 | #include <exception> | ||
| 6 | #include <vector> | ||
| 7 | |||
| 8 | #include "vlasova_a_matrix_multiply_ccs/common/include/common.hpp" | ||
| 9 | |||
| 10 | namespace vlasova_a_matrix_multiply_ccs { | ||
| 11 | |||
| 12 | namespace { | ||
| 13 | constexpr double kEpsilon = 1e-10; | ||
| 14 | } // namespace | ||
| 15 | |||
| 16 |
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24 | VlasovaAMatrixMultiplySEQ::VlasovaAMatrixMultiplySEQ(const InType &in) { |
| 17 | SetTypeOfTask(GetStaticTypeOfTask()); | ||
| 18 | GetInput() = in; | ||
| 19 | 24 | GetOutput() = SparseMatrixCCS{}; | |
| 20 | 24 | } | |
| 21 | |||
| 22 | 24 | bool VlasovaAMatrixMultiplySEQ::ValidationImpl() { | |
| 23 | const auto &[a, b] = GetInput(); | ||
| 24 |
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24 | return (a.rows > 0 && a.cols > 0 && b.rows > 0 && b.cols > 0 && a.cols == b.rows); |
| 25 | } | ||
| 26 | |||
| 27 | 24 | bool VlasovaAMatrixMultiplySEQ::PreProcessingImpl() { | |
| 28 | 24 | return true; | |
| 29 | } | ||
| 30 | |||
| 31 | 24 | void VlasovaAMatrixMultiplySEQ::TransposeMatrix(const SparseMatrixCCS &a, SparseMatrixCCS &at) { | |
| 32 | 24 | at.rows = a.cols; | |
| 33 | 24 | at.cols = a.rows; | |
| 34 | 24 | at.nnz = a.nnz; | |
| 35 | |||
| 36 |
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24 | if (a.nnz == 0) { |
| 37 | at.values.clear(); | ||
| 38 | at.row_indices.clear(); | ||
| 39 | ✗ | at.col_ptrs.assign(at.cols + 1, 0); | |
| 40 | ✗ | return; | |
| 41 | } | ||
| 42 | |||
| 43 | 24 | std::vector<int> row_count(at.cols, 0); | |
| 44 |
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6215 | for (int i = 0; i < a.nnz; i++) { |
| 45 | 6191 | row_count[a.row_indices[i]]++; | |
| 46 | } | ||
| 47 | |||
| 48 |
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24 | at.col_ptrs.resize(at.cols + 1); |
| 49 | 24 | at.col_ptrs[0] = 0; | |
| 50 |
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1304 | for (int i = 0; i < at.cols; i++) { |
| 51 | 1280 | at.col_ptrs[i + 1] = at.col_ptrs[i] + row_count[i]; | |
| 52 | } | ||
| 53 | |||
| 54 |
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24 | at.values.resize(a.nnz); |
| 55 |
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24 | at.row_indices.resize(a.nnz); |
| 56 | |||
| 57 |
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24 | std::vector<int> current_pos(at.cols, 0); |
| 58 |
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1304 | for (int col = 0; col < a.cols; col++) { |
| 59 |
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7471 | for (int i = a.col_ptrs[col]; i < a.col_ptrs[col + 1]; i++) { |
| 60 | 6191 | int row = a.row_indices[i]; | |
| 61 | 6191 | double val = a.values[i]; | |
| 62 | |||
| 63 | 6191 | int pos = at.col_ptrs[row] + current_pos[row]; | |
| 64 | 6191 | at.values[pos] = val; | |
| 65 | 6191 | at.row_indices[pos] = col; | |
| 66 | 6191 | current_pos[row]++; | |
| 67 | } | ||
| 68 | } | ||
| 69 | } | ||
| 70 | |||
| 71 | namespace { | ||
| 72 | |||
| 73 | 1280 | void ProcessColumnSEQ(const SparseMatrixCCS &at, const SparseMatrixCCS &b, int col_index, std::vector<double> &temp_row, | |
| 74 | std::vector<int> &row_marker, std::vector<double> &res_val, std::vector<int> &res_row_ind) { | ||
| 75 |
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7568 | for (int k = b.col_ptrs[col_index]; k < b.col_ptrs[col_index + 1]; k++) { |
| 76 | 6288 | int row_b = b.row_indices[k]; | |
| 77 | 6288 | double val_b = b.values[k]; | |
| 78 | |||
| 79 |
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37113 | for (int idx = at.col_ptrs[row_b]; idx < at.col_ptrs[row_b + 1]; idx++) { |
| 80 |
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30825 | int row_a = at.row_indices[idx]; |
| 81 | 30825 | double val_a = at.values[idx]; | |
| 82 | |||
| 83 |
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30825 | if (row_marker[row_a] != col_index) { |
| 84 | 26197 | row_marker[row_a] = col_index; | |
| 85 | 26197 | temp_row[row_a] = val_a * val_b; | |
| 86 | } else { | ||
| 87 | 4628 | temp_row[row_a] += val_a * val_b; | |
| 88 | } | ||
| 89 | } | ||
| 90 | } | ||
| 91 | |||
| 92 |
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102080 | for (size_t i = 0; i < temp_row.size(); i++) { |
| 93 |
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100800 | if (row_marker[i] == col_index && std::abs(temp_row[i]) > kEpsilon) { |
| 94 | res_val.push_back(temp_row[i]); | ||
| 95 | 26197 | res_row_ind.push_back(static_cast<int>(i)); | |
| 96 | } | ||
| 97 | } | ||
| 98 | 1280 | } | |
| 99 | |||
| 100 | } // namespace | ||
| 101 | |||
| 102 | 24 | void VlasovaAMatrixMultiplySEQ::MultiplyMatrices(const SparseMatrixCCS &a, const SparseMatrixCCS &b, | |
| 103 | SparseMatrixCCS &c) { | ||
| 104 | 24 | SparseMatrixCCS at; | |
| 105 |
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24 | TransposeMatrix(a, at); |
| 106 | |||
| 107 | 24 | c.rows = a.rows; | |
| 108 | 24 | c.cols = b.cols; | |
| 109 |
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24 | c.col_ptrs.push_back(0); |
| 110 | |||
| 111 |
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24 | std::vector<double> temp_row(c.rows, 0.0); |
| 112 |
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24 | std::vector<int> row_marker(c.rows, -1); |
| 113 | |||
| 114 |
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1304 | for (int j = 0; j < b.cols; j++) { |
| 115 |
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1280 | ProcessColumnSEQ(at, b, j, temp_row, row_marker, c.values, c.row_indices); |
| 116 |
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1280 | c.col_ptrs.push_back(static_cast<int>(c.values.size())); |
| 117 | } | ||
| 118 | |||
| 119 |
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24 | c.nnz = static_cast<int>(c.values.size()); |
| 120 | 24 | } | |
| 121 | |||
| 122 |
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24 | bool VlasovaAMatrixMultiplySEQ::RunImpl() { |
| 123 | const auto &[a, b] = GetInput(); | ||
| 124 | |||
| 125 | try { | ||
| 126 | 24 | SparseMatrixCCS c; | |
| 127 |
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24 | MultiplyMatrices(a, b, c); |
| 128 |
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24 | GetOutput() = c; |
| 129 | return true; | ||
| 130 |
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24 | } catch (const std::exception &) { |
| 131 | return false; | ||
| 132 | ✗ | } | |
| 133 | } | ||
| 134 | |||
| 135 | 24 | bool VlasovaAMatrixMultiplySEQ::PostProcessingImpl() { | |
| 136 | const auto &c = GetOutput(); | ||
| 137 |
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24 | return c.rows > 0 && c.cols > 0 && c.col_ptrs.size() == static_cast<size_t>(c.cols) + 1; |
| 138 | } | ||
| 139 | |||
| 140 | } // namespace vlasova_a_matrix_multiply_ccs | ||
| 141 |