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Гусева Алена. Технология SEQ-MPI. Сумма элементов матрицы по столбцам. Вариант 12 #11
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Merge branch 'learning-process:master' into guseva_a_matrix_sums
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Merge branch 'learning-process:master' into guseva_a_matrix_sums
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| #pragma once | ||
|
|
||
| #include <tuple> | ||
|
|
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| #include "task/include/task.hpp" | ||
|
|
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| namespace guseva_a_matrix_sums { | ||
| using InType = std::tuple<uint32_t, uint32_t, std::vector<double>>; | ||
| using OutType = std::vector<double>; | ||
| using TestType = std::string; | ||
| using BaseTask = ppc::task::Task<InType, OutType>; | ||
|
|
||
| } // namespace guseva_a_matrix_sums |
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| { | ||
| "student": { | ||
| "first_name": "Алёна", | ||
| "last_name": "Гусева", | ||
| "middle_name": "Алексеевна", | ||
| "group_number": "3823Б1ФИ2", | ||
| "task_number": "1" | ||
| } | ||
| } |
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| #pragma once | ||
|
|
||
| #include "guseva_a_matrix_sums/common/include/common.hpp" | ||
| #include "task/include/task.hpp" | ||
|
|
||
| namespace guseva_a_matrix_sums { | ||
|
|
||
| class GusevaAMatrixSumsMPI : public BaseTask { | ||
| public: | ||
| static constexpr ppc::task::TypeOfTask GetStaticTypeOfTask() { | ||
| return ppc::task::TypeOfTask::kMPI; | ||
| } | ||
| explicit GusevaAMatrixSumsMPI(const InType &in); | ||
|
|
||
| private: | ||
| bool ValidationImpl() override; | ||
| bool PreProcessingImpl() override; | ||
| bool RunImpl() override; | ||
| bool PostProcessingImpl() override; | ||
| }; | ||
|
|
||
| } // namespace guseva_a_matrix_sums |
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| #include "guseva_a_matrix_sums/mpi/include/ops_mpi.hpp" | ||
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| #include <mpi.h> | ||
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| #include <cstdint> | ||
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| namespace guseva_a_matrix_sums { | ||
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| GusevaAMatrixSumsMPI::GusevaAMatrixSumsMPI(const InType &in) { | ||
| SetTypeOfTask(GetStaticTypeOfTask()); | ||
| GetInput() = in; | ||
| GetOutput() = {}; | ||
| } | ||
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| bool GusevaAMatrixSumsMPI::ValidationImpl() { | ||
| return (static_cast<uint64_t>(std::get<0>(GetInput())) * std::get<1>(GetInput()) == std::get<2>(GetInput()).size()) && | ||
| (GetOutput().empty()); | ||
| } | ||
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| bool GusevaAMatrixSumsMPI::PreProcessingImpl() { | ||
| GetOutput().clear(); | ||
| GetOutput().resize(std::get<1>(GetInput()), 0.0); | ||
| return true; | ||
| } | ||
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| bool GusevaAMatrixSumsMPI::RunImpl() { | ||
| int rows = 0; | ||
| int columns = 0; | ||
| std::vector<double> matrix; | ||
| int wsize = 0; | ||
| int rank = 0; | ||
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| MPI_Comm_size(MPI_COMM_WORLD, &wsize); | ||
| MPI_Comm_rank(MPI_COMM_WORLD, &rank); | ||
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| if (rank == 0) { | ||
| rows = static_cast<int>(std::get<0>(GetInput())); | ||
| columns = static_cast<int>(std::get<1>(GetInput())); | ||
| matrix = std::get<2>(GetInput()); | ||
| } | ||
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| MPI_Bcast(&rows, 1, MPI_INT, 0, MPI_COMM_WORLD); | ||
| MPI_Bcast(&columns, 1, MPI_INT, 0, MPI_COMM_WORLD); | ||
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| uint32_t rows_per_proc = rows / wsize; | ||
| uint32_t remainder = rows % wsize; | ||
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| std::vector<int> displs(wsize, 0); | ||
| std::vector<int> counts; | ||
| counts.reserve(wsize); | ||
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| if (rank == 0) { | ||
| for (int rnk = 0; rnk < wsize; rnk++) { | ||
| uint32_t start_row = (rnk * rows_per_proc) + std::min(static_cast<uint32_t>(rnk), remainder); | ||
| uint32_t end_row = ((rnk + 1) * rows_per_proc) + std::min(static_cast<uint32_t>(rnk + 1), remainder); | ||
| uint32_t start_pos = start_row * columns; | ||
| uint32_t end_pos = end_row * columns; | ||
| counts.push_back(static_cast<int>(end_pos - start_pos)); | ||
| for (int i = rnk + 1; i < wsize; i++) { | ||
| displs[i] += counts.back(); | ||
| } | ||
| } | ||
| } | ||
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| MPI_Bcast(counts.data(), static_cast<int>(counts.size()), MPI_INT, 0, MPI_COMM_WORLD); | ||
| MPI_Bcast(displs.data(), static_cast<int>(displs.size()), MPI_INT, 0, MPI_COMM_WORLD); | ||
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| uint32_t start_row = (rank * rows_per_proc) + std::min(static_cast<uint32_t>(rank), remainder); | ||
| uint32_t end_row = ((rank + 1) * rows_per_proc) + std::min(static_cast<uint32_t>(rank + 1), remainder); | ||
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| uint32_t start_pos = start_row * columns; | ||
| uint32_t end_pos = end_row * columns; | ||
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| std::vector<double> slice(end_pos - start_pos, 0); | ||
| MPI_Scatterv(matrix.data(), counts.data(), displs.data(), MPI_DOUBLE, slice.data(), counts[rank], MPI_DOUBLE, 0, | ||
| MPI_COMM_WORLD); | ||
| std::vector<double> local_sums(columns, 0); | ||
| for (uint32_t i = 0; i < end_pos - start_pos; i++) { | ||
| local_sums[i % columns] += slice[i]; | ||
| } | ||
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| std::vector<double> global_sums(columns, 0); | ||
| MPI_Reduce(local_sums.data(), global_sums.data(), columns, MPI_DOUBLE, MPI_SUM, 0, MPI_COMM_WORLD); | ||
| MPI_Bcast(global_sums.data(), columns, MPI_DOUBLE, 0, MPI_COMM_WORLD); | ||
| GetOutput().assign(global_sums.begin(), global_sums.end()); | ||
| return true; | ||
| } | ||
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| bool GusevaAMatrixSumsMPI::PostProcessingImpl() { | ||
| return true; | ||
| } | ||
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| } // namespace guseva_a_matrix_sums | ||
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,22 @@ | ||
| #pragma once | ||
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| #include "guseva_a_matrix_sums/common/include/common.hpp" | ||
| #include "task/include/task.hpp" | ||
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| namespace guseva_a_matrix_sums { | ||
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| class GusevaAMatrixSumsSEQ : public BaseTask { | ||
| public: | ||
| static constexpr ppc::task::TypeOfTask GetStaticTypeOfTask() { | ||
| return ppc::task::TypeOfTask::kSEQ; | ||
| } | ||
| explicit GusevaAMatrixSumsSEQ(const InType &in); | ||
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| private: | ||
| bool ValidationImpl() override; | ||
| bool PreProcessingImpl() override; | ||
| bool RunImpl() override; | ||
| bool PostProcessingImpl() override; | ||
| }; | ||
|
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| } // namespace guseva_a_matrix_sums |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,38 @@ | ||
| #include "guseva_a_matrix_sums/seq/include/ops_seq.hpp" | ||
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| namespace guseva_a_matrix_sums { | ||
|
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| GusevaAMatrixSumsSEQ::GusevaAMatrixSumsSEQ(const InType &in) { | ||
| SetTypeOfTask(GetStaticTypeOfTask()); | ||
| GetInput() = in; | ||
| GetOutput() = {}; | ||
| } | ||
|
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| bool GusevaAMatrixSumsSEQ::ValidationImpl() { | ||
| return (static_cast<uint64_t>(std::get<0>(GetInput())) * std::get<1>(GetInput()) == std::get<2>(GetInput()).size()) && | ||
| (GetOutput().empty()); | ||
| } | ||
|
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| bool GusevaAMatrixSumsSEQ::PreProcessingImpl() { | ||
| GetOutput().clear(); | ||
| GetOutput().resize(std::get<1>(GetInput()), 0.0); | ||
| return true; | ||
| } | ||
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| bool GusevaAMatrixSumsSEQ::RunImpl() { | ||
| auto &matrix = std::get<2>(GetInput()); | ||
| auto &columns = std::get<1>(GetInput()); | ||
| auto &rows = std::get<0>(GetInput()); | ||
| for (uint32_t i = 0; i < rows; i++) { | ||
| for (uint32_t j = 0; j < columns; j++) { | ||
| GetOutput()[j] += matrix[(i * columns) + j]; | ||
| } | ||
| } | ||
| return true; | ||
| } | ||
|
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| bool GusevaAMatrixSumsSEQ::PostProcessingImpl() { | ||
| return true; | ||
| } | ||
|
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| } // namespace guseva_a_matrix_sums |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,7 @@ | ||
| { | ||
| "tasks_type": "processes", | ||
| "tasks": { | ||
| "mpi": "enabled", | ||
| "seq": "enabled" | ||
| } | ||
| } |
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countsis only filled on rank 0 but other ranks keep it empty. The subsequentMPI_Bcast(counts.data(), counts.size(), MPI_INT, 0, MPI_COMM_WORLD)therefore broadcastswsizeelements from the root while receivers providecount=0and a null buffer, which violates MPI’s requirement that all ranks pass the same element count and leaves no storage for the incoming data. On multi‑process runs this results in an MPI error or crash andcounts[rank]is undefined beforeMPI_Scatterv. The vector should be resized towsize(and populated via the broadcast) before callingMPI_Bcast.Useful? React with 👍 / 👎.