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|---|---|---|---|
| 1 | #include "kosolapov_v_max_values_in_col_matrix/mpi/include/ops_mpi.hpp" | ||
| 2 | |||
| 3 | #include <mpi.h> | ||
| 4 | |||
| 5 | #include <algorithm> | ||
| 6 | #include <cstddef> | ||
| 7 | #include <limits> | ||
| 8 | #include <vector> | ||
| 9 | |||
| 10 | #include "kosolapov_v_max_values_in_col_matrix/common/include/common.hpp" | ||
| 11 | |||
| 12 | namespace kosolapov_v_max_values_in_col_matrix { | ||
| 13 | |||
| 14 |
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26 | KosolapovVMaxValuesInColMatrixMPI::KosolapovVMaxValuesInColMatrixMPI(const InType &in) { |
| 15 | SetTypeOfTask(GetStaticTypeOfTask()); | ||
| 16 |
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26 | GetInput() = InType(in); |
| 17 | GetOutput() = {}; | ||
| 18 | 26 | } | |
| 19 | |||
| 20 | 26 | bool KosolapovVMaxValuesInColMatrixMPI::ValidationImpl() { | |
| 21 | 26 | int rank = 0; | |
| 22 | 26 | MPI_Comm_rank(MPI_COMM_WORLD, &rank); | |
| 23 | |||
| 24 |
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26 | if (rank == 0) { |
| 25 | const auto &matrix = GetInput(); | ||
| 26 |
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13 | if (matrix.empty()) { |
| 27 | return false; | ||
| 28 | } | ||
| 29 |
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67 | for (size_t i = 0; i < matrix.size() - 1; i++) { |
| 30 |
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54 | if ((matrix[i].size() != matrix[i + 1].size()) || (matrix[i].empty())) { |
| 31 | return false; | ||
| 32 | } | ||
| 33 | } | ||
| 34 | } | ||
| 35 | 26 | return (GetOutput().empty()); | |
| 36 | } | ||
| 37 | |||
| 38 |
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26 | bool KosolapovVMaxValuesInColMatrixMPI::PreProcessingImpl() { |
| 39 | GetOutput().clear(); | ||
| 40 | |||
| 41 | 26 | int rank = 0; | |
| 42 | 26 | MPI_Comm_rank(MPI_COMM_WORLD, &rank); | |
| 43 |
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26 | if (rank == 0) { |
| 44 | const auto &matrix = GetInput(); | ||
| 45 |
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13 | if (!matrix.empty() && !matrix[0].empty()) { |
| 46 | 13 | GetOutput().resize(matrix[0].size()); | |
| 47 | } | ||
| 48 | } | ||
| 49 | 26 | return true; | |
| 50 | } | ||
| 51 | |||
| 52 | 26 | bool KosolapovVMaxValuesInColMatrixMPI::RunImpl() { | |
| 53 | 26 | int processes_count = 0; | |
| 54 | 26 | int rank = 0; | |
| 55 | 26 | MPI_Comm_size(MPI_COMM_WORLD, &processes_count); | |
| 56 | 26 | MPI_Comm_rank(MPI_COMM_WORLD, &rank); | |
| 57 | |||
| 58 | 26 | std::vector<std::vector<int>> local_matrix; | |
| 59 | 26 | int rows = 0; | |
| 60 | 26 | int columns = 0; | |
| 61 |
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26 | if (rank == 0) { |
| 62 | const auto &matrix = GetInput(); | ||
| 63 | 13 | rows = static_cast<int>(matrix.size()); | |
| 64 | 13 | columns = static_cast<int>(matrix[0].size()); | |
| 65 | } | ||
| 66 |
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26 | MPI_Bcast(&rows, 1, MPI_INT, 0, MPI_COMM_WORLD); |
| 67 |
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26 | MPI_Bcast(&columns, 1, MPI_INT, 0, MPI_COMM_WORLD); |
| 68 | |||
| 69 | 26 | const int rows_per_proc = rows / processes_count; | |
| 70 | 26 | const int remainder = rows % processes_count; | |
| 71 |
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26 | const int start = (rank * rows_per_proc) + std::min(rank, remainder); |
| 72 |
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26 | const int end = start + rows_per_proc + (rank < remainder ? 1 : 0); |
| 73 | 26 | const int local_rows = end - start; | |
| 74 | |||
| 75 |
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26 | if (rank == 0) { |
| 76 |
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13 | DistributeDataFromRoot(local_matrix, start, local_rows, columns, processes_count, rows_per_proc, remainder); |
| 77 | } else { | ||
| 78 |
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13 | local_matrix.resize(local_rows); |
| 79 |
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43 | for (int i = 0; i < local_rows; i++) { |
| 80 |
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30 | local_matrix[i].resize(columns); |
| 81 |
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30 | MPI_Recv(local_matrix[i].data(), columns, MPI_INT, 0, i, MPI_COMM_WORLD, MPI_STATUS_IGNORE); |
| 82 | } | ||
| 83 | } | ||
| 84 |
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26 | auto local_maxs = CalculateLocalMax(local_matrix, columns); |
| 85 |
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26 | std::vector<int> global_maxs(columns); |
| 86 |
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26 | MPI_Allreduce(local_maxs.data(), global_maxs.data(), columns, MPI_INT, MPI_MAX, MPI_COMM_WORLD); |
| 87 |
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26 | GetOutput() = global_maxs; |
| 88 | 26 | return true; | |
| 89 | 26 | } | |
| 90 | |||
| 91 | 26 | bool KosolapovVMaxValuesInColMatrixMPI::PostProcessingImpl() { | |
| 92 | 26 | return true; | |
| 93 | } | ||
| 94 | |||
| 95 | 13 | void KosolapovVMaxValuesInColMatrixMPI::DistributeDataFromRoot(std::vector<std::vector<int>> &local_matrix, int start, | |
| 96 | int local_rows, int columns, int processes_count, | ||
| 97 | int rows_per_proc, int remainder) { | ||
| 98 | const auto &matrix = GetInput(); | ||
| 99 | 13 | local_matrix.resize(local_rows); | |
| 100 | |||
| 101 |
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50 | for (int i = 0; i < local_rows; i++) { |
| 102 | 37 | local_matrix[i] = matrix[start + i]; | |
| 103 | } | ||
| 104 | |||
| 105 |
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26 | for (int proc = 1; proc < processes_count; proc++) { |
| 106 |
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13 | const int proc_start = (proc * rows_per_proc) + std::min(proc, remainder); |
| 107 |
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13 | const int proc_end = proc_start + rows_per_proc + (proc < remainder ? 1 : 0); |
| 108 | 13 | const int proc_rows_count = proc_end - proc_start; | |
| 109 | |||
| 110 |
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43 | for (int i = 0; i < proc_rows_count; i++) { |
| 111 | 30 | MPI_Send(matrix[proc_start + i].data(), columns, MPI_INT, proc, i, MPI_COMM_WORLD); | |
| 112 | } | ||
| 113 | } | ||
| 114 | 13 | } | |
| 115 | 26 | std::vector<int> KosolapovVMaxValuesInColMatrixMPI::CalculateLocalMax(const std::vector<std::vector<int>> &matrix, | |
| 116 | const int columns) { | ||
| 117 | 26 | std::vector<int> local_maxs(columns, std::numeric_limits<int>::min()); | |
| 118 |
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93 | for (const auto &row : matrix) { |
| 119 |
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670 | for (int i = 0; i < columns; i++) { |
| 120 |
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927 | local_maxs[i] = std::max(row[i], local_maxs[i]); |
| 121 | } | ||
| 122 | } | ||
| 123 | 26 | return local_maxs; | |
| 124 | } | ||
| 125 | } // namespace kosolapov_v_max_values_in_col_matrix | ||
| 126 |