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# Default ignored files
/shelf/
/workspace.xml
# Editor-based HTTP Client requests
/httpRequests/
# Datasource local storage ignored files
/dataSources/
/dataSources.local.xml
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Uebung5
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</project>
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<?xml version="1.0" encoding="UTF-8"?>
<project version="4">
<component name="CMakePythonSetting">
<option name="pythonIntegrationState" value="YES" />
</component>
<component name="CMakeWorkspace" PROJECT_DIR="$PROJECT_DIR$" />
</project>
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<?xml version="1.0" encoding="UTF-8"?>
<project version="4">
<component name="ProjectModuleManager">
<modules>
<module fileurl="file://$PROJECT_DIR$/.idea/parallel2.iml" filepath="$PROJECT_DIR$/.idea/parallel2.iml" />
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</component>
</project>
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<?xml version="1.0" encoding="UTF-8"?>
<module classpath="CMake" type="CPP_MODULE" version="4" />
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<?xml version="1.0" encoding="UTF-8"?>
<project version="4">
<component name="VcsDirectoryMappings">
<mapping directory="$PROJECT_DIR$/.." vcs="Git" />
</component>
</project>
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cmake_minimum_required(VERSION 3.15)
project(Uebung5)
set(CMAKE_CXX_STANDARD 17)
set(CMAKE_CXX_STANDARD_REQUIRED ON)
# OpenMP aktivieren
find_package(OpenMP REQUIRED)
if(OpenMP_CXX_FOUND)
message(STATUS "OpenMP found")
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} ${OpenMP_CXX_FLAGS}")
endif()
# Executable erstellen
add_executable(parallel2 main.cpp)
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#include <iostream>
#include <vector>
#include <cstdlib>
#include <ctime>
#include <chrono>
#include <cmath>
#include <omp.h>
// Matrizen erzeugen
void generateRandomMatrices(int n,
std::vector<std::vector<double>>& A,
std::vector<std::vector<double>>& B,
double min_val = 0.0,
double max_val = 10.0)
{
std::srand(static_cast<unsigned int>(std::time(nullptr)));
A.resize(n, std::vector<double>(n));
B.resize(n, std::vector<double>(n));
for (int i = 0; i < n; ++i)
for (int j = 0; j < n; ++j)
{
double r1 = static_cast<double>(std::rand()) / RAND_MAX;
double r2 = static_cast<double>(std::rand()) / RAND_MAX;
A[i][j] = min_val + r1 * (max_val - min_val);
B[i][j] = min_val + r2 * (max_val - min_val);
}
}
// Seriell
std::vector<std::vector<double>> matmul_serial(const std::vector<std::vector<double>>& A,
const std::vector<std::vector<double>>& B)
{
int n = A.size();
int m = B[0].size();
int p = B.size();
std::vector<std::vector<double>> C(n, std::vector<double>(m, 0.0));
for (int i = 0; i < n; ++i)
for (int j = 0; j < m; ++j)
for (int k = 0; k < p; ++k)
C[i][j] += A[i][k] * B[k][j];
return C;
}
// Parallele Zeilenzerlegung
std::vector<std::vector<double>> matmul_parallel_rows(const std::vector<std::vector<double>>& A,
const std::vector<std::vector<double>>& B,
int numThreads)
{
int n = A.size();
int m = B[0].size();
int p = B.size();
std::vector<std::vector<double>> C(n, std::vector<double>(m, 0.0));
#pragma omp parallel for num_threads(numThreads)
for (int i = 0; i < n; ++i)
{
std::vector<double> row(m, 0.0);
for (int j = 0; j < m; ++j)
{
double sum = 0.0;
for (int k = 0; k < p; ++k)
sum += A[i][k] * B[k][j]; //verhindert überschreibuung
row[j] = sum;
}
C[i] = row;
}
return C;
}
// Parallele Spaltenzerlegung
std::vector<std::vector<double>> matmul_parallel_cols(const std::vector<std::vector<double>>& A,
const std::vector<std::vector<double>>& B,
int numThreads)
{
int n = A.size();
int m = B[0].size();
int p = B.size();
std::vector<std::vector<double>> C(n, std::vector<double>(m, 0.0));
#pragma omp parallel for num_threads(numThreads)
for (int j = 0; j < m; ++j)
{
for (int i = 0; i < n; ++i)
{
double sum = 0.0;
for (int k = 0; k < p; ++k)
sum += A[i][k] * B[k][j]; //Zwischengepeichert
C[i][j] = sum;
}
}
return C;
}
// Blockzerlegung
std::vector<std::vector<double>> matmul_block(const std::vector<std::vector<double>>& A,
const std::vector<std::vector<double>>& B,
int blockSize,
int numThreads)
{
int n = A.size();
int m = B[0].size();
int p = B.size();
std::vector<std::vector<double>> C(n, std::vector<double>(m, 0.0));
#pragma omp parallel for collapse(2) num_threads(numThreads)
for (int ii = 0; ii < n; ii += blockSize)
for (int jj = 0; jj < m; jj += blockSize)
{
for (int i = ii; i < std::min(ii + blockSize, n); ++i)
for (int j = jj; j < std::min(jj + blockSize, m); ++j)
{
double sum = 0.0;
for (int k = 0; k < p; ++k)
sum += A[i][k] * B[k][j];
C[i][j] = sum;
}
}
return C;
}
// Matrix ausgeben
void printMatrix(const std::vector<std::vector<double>>& M, const std::string& name)
{
std::cout << name << " (" << M.size() << "x" << (M.empty() ? 0 : M[0].size()) << "):\n";
for (const auto& row : M)
{
for (double val : row)
std::cout << val << "\t";
std::cout << "\n";
}
std::cout << "\n";
}
//Matrix Vergleich (Komponentenweise)
bool compareMatrices(const std::vector<std::vector<double>>& A,
const std::vector<std::vector<double>>& B)
{
if (A.size() != B.size() || A[0].size() != B[0].size())
return false;
for (size_t i = 0; i < A.size(); ++i)
for (size_t j = 0; j < A[0].size(); ++j)
if (std::abs(A[i][j] - B[i][j]) > 1e-9)
return false;
return true;
}
int main()
{
int N = 4; // für Ausgabe kleiner Matrizen <5
int numThreads = omp_get_max_threads();
if (numThreads == 0) numThreads = 4;
std::vector<std::vector<double>> A, B;
generateRandomMatrices(N, A, B);
if (N < 5)
{
printMatrix(A, "Matrix A");
printMatrix(B, "Matrix B");
}
// Serielle Berechnung
auto start = std::chrono::steady_clock::now();
auto C_serial = matmul_serial(A, B);
auto end = std::chrono::steady_clock::now();
double timeSerial = std::chrono::duration<double>(end - start).count();
std::cout << "Seriell: " << timeSerial << " s\n";
if (N < 5)
printMatrix(C_serial, "C_serial");
// Zeilenparallel
start = std::chrono::steady_clock::now();
auto C_rows = matmul_parallel_rows(A, B, numThreads);
end = std::chrono::steady_clock::now();
double timeRows = std::chrono::duration<double>(end - start).count();
std::cout << "Parallel Zeilen: " << timeRows << " s | "
<< (compareMatrices(C_serial, C_rows) ? "Match" : "Mismatch") << "\n";
if (N < 5)
printMatrix(C_rows, "C_rows");
// Spaltenparallel
start = std::chrono::steady_clock::now();
auto C_cols = matmul_parallel_cols(A, B, numThreads);
end = std::chrono::steady_clock::now();
double timeCols = std::chrono::duration<double>(end - start).count();
std::cout << "Parallel Spalten: " << timeCols << " s | "
<< (compareMatrices(C_serial, C_cols) ? "Match" : "Mismatch") << "\n";
if (N < 5)
printMatrix(C_cols, "C_cols");
// Blockparallel
int blockSize = 2; // für kleine N passend
start = std::chrono::steady_clock::now();
auto C_block = matmul_block(A, B, blockSize, numThreads);
end = std::chrono::steady_clock::now();
double timeBlock = std::chrono::duration<double>(end - start).count();
std::cout << "Parallel Block (" << blockSize << "x" << blockSize << "): "
<< timeBlock << " s | "
<< (compareMatrices(C_serial, C_block) ? "Match" : "Mismatch") << "\n";
if (N < 5)
printMatrix(C_block, "C_block");
return 0;
}
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