(Work in Progress)
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GCC10
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GNU Build System (a.k.a. Make)
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C++20
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fast open-source formatting library
{fmt}
(Doxygen was used to generate documentation, can be safely ignored)
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Copy codes below, save it in a file
testlib.cppin a directory parallel to the SparseTensor directory. -
To build, use the following makefile
CXX=g++-10 CXXFLAGS=-std=c++2a -MD sparse: testlib.o SparseTensor/src/SparseTensor.o >-------$(CXX) -o $@ $^ -lfmt clean: >-------rm -f *.o sparse SparseTensor/src/*.o -include *.d -include SparseTensor/src/*.dexecute make from terminal to build. Use make clean to clean auxiliary files (if needed).
- To run, execute
./sparseor./sparse >file.txt 2>&1to redirect all terminal output to a file. (Demo 1) Or./sparse 2>&1 | tee file.txtto redirect all terminal output to a file (Demo 2)
#include"SparseTensor/include/matrix.h" #include"SparseTensor/include/SparseTensor.h" #include"SparseTensor/include/util.h" #include"SparseTensor/include/Timer.h" #include<random> #include<fstream> #include <iostream> #include <vector> using std::vector; constexpr int M = 5; constexpr int N = 5; using SparseTensor::SparseMatrixEntry; using SparseTensor::operator<<; using SparseTensor::nested_print; using SparseTensor::MatMultiply; using SparseTensor::SparseMul; using SparseTensor::KroneckersProduct; using SparseTensor::KroneckersOuterProduct; using SparseTensor::matrix; using SparseTensor::Timer; using SparseTensor::Matrix; using SparseTensor::Tensor; int main() { std::cerr << "Convert dense data structure to sparse" << "\n"; vector<vector<int>> a {{{0, 3, 0, 0, 0}, {22, 0, 0, 0, 17}, {7, 5, 0, 1, 0}, {0, 0, 0, 0, 0}, {0, 0, 14, 0, 8}}}; vector<SparseMatrixEntry> vs; vs.emplace_back(SparseMatrixEntry(0, 1, a[0][1])); vs.emplace_back(SparseMatrixEntry(1, 0, a[1][0])); vs.emplace_back(SparseMatrixEntry(1, 4, a[1][4])); vs.emplace_back(SparseMatrixEntry(2, 0, a[2][0])); vs.emplace_back(SparseMatrixEntry(2, 1, a[2][1])); vs.emplace_back(SparseMatrixEntry(2, 3, a[2][3])); vs.emplace_back(SparseMatrixEntry(4, 3, a[4][3])); vs.emplace_back(SparseMatrixEntry(4, 4, a[4][4])); std::cout << vs << "\n"; std::cerr << "Convert sparse data structure to dense" << "\n"; vector<SparseMatrixEntry> d; d.emplace_back(SparseMatrixEntry(0, 1, 3)); d.emplace_back(SparseMatrixEntry(1, 0, 22)); d.emplace_back(SparseMatrixEntry(1, 4, 17)); d.emplace_back(SparseMatrixEntry(2, 0, 7)); d.emplace_back(SparseMatrixEntry(2, 1, 5)); d.emplace_back(SparseMatrixEntry(2, 3, 1)); d.emplace_back(SparseMatrixEntry(4, 2, 14)); d.emplace_back(SparseMatrixEntry(4, 4, 8)); std::cout << d; std::cout << "\n"; vector<std::vector<int>> vd(M, vector <int> (N, 0)); vd[0][1] = d[0].value; vd[1][0] = d[1].value; vd[1][4] = d[2].value; vd[2][0] = d[3].value; vd[2][1] = d[4].value; vd[2][3] = d[5].value; vd[4][2] = d[6].value; vd[4][4] = d[7].value; std::cout << vd; std::cerr << "Perform matrix multiplication of 2D arrays: " << "\n"; vector<vector<Value>> A {{{0, 3, 0, 0, 0}, {22, 0, 0, 0, 17}, {7, 5, 0, 1, 0}, {0, 0, 0, 0, 0}, {0, 0, 14, 0, 8}}}; vector<vector<Value>> B {{{0, 3, 0, 0, 0}, {0, 0, 0, 0, 17}, {7, 5, 0, 1, 0}, {0, 0, 0, 0, 0}, {0, 0, 14, 0, 8}}}; vector<vector<Value>> C = SparseMul(A, B); std::cout << C; Matrix D = MatMultiply(A, B); std::cout << D; std::cerr << "Compute kronecker products of 2 multidimensional arrays: " << "\n"; Matrix m1{{1, 2}, {3, 4}, {1, 0}}; Matrix m2{{0, 5, 2}, {6, 7, 3}}; Matrix v(KroneckersProduct(m1, m2)); std::cout << v; std::cerr << "Compute kronecker outer products of 2 multidimensional arrays: " << "\n"; Tensor m(KroneckersOuterProduct(m1, m2)); nested_print(std::span(m)); std::random_device rd; std::mt19937 gen(rd()); std::uniform_real_distribution<> dis(1.0, 10.0); vector<vector<double>> Matrix(5, vector<double>(7, 0)); std::ofstream file("matrix.txt"); for (auto &row : Matrix){ for (auto &col : row){ col = dis(gen); file << std::setw(4) << col; } file << '\n'; } matrix mtx { { 1.0, 2.0 }, { 4.0, 5.0 }, { 8.0, 9.0 } } ; matrix mty { { 3.0, 2.0, 1.0 }, { 4.0, 2.0, 9.0 } } ; std::cerr << "Measure time taken for naive Matrix multiplication: " << "\n"; Timer t; matrix mtz = mtx * mty; std::cerr << "Measure time taken for printing naive Matrix multiplication (fmt): " << "\n"; Timer tt; for (int i=0; i!=mtz.num_rows(); ++i) { for (int j=0; j!=mtz.num_cols(); ++j) { std::cout << mtz(i,j) << " "; } std::cout << "\n"; } } //g++-10 -std=c++2a -o sparse testlib.cpp SparseTensor/src/SparseTensor.cpp -lfmt#include"SparseTensor/include/matrix.h" #include"SparseTensor/include/SparseTensor.h" #include"SparseTensor/include/util.h" #include"SparseTensor/include/Timer.h" #include<random> #include<iomanip> #include<fstream> #include <iostream> #include <vector> using std::cout; using std::vector; constexpr int M = 5; constexpr int N = 5; constexpr int K = 8; using SparseTensor::SparseMatrixEntry; using SparseTensor::operator<<; using SparseTensor::nested_print; using SparseTensor::MatMultiply; using SparseTensor::SparseMul; using SparseTensor::KroneckersProduct; using SparseTensor::KroneckersOuterProduct; using SparseTensor::matrix; using SparseTensor::Timer; using SparseTensor::Matrix; using SparseTensor::Tensor; void case1(); void case2(); void case3(); void case4(); void case5(); void case6(); int main() { int choice; do { cout << "\n"; cout << "Please choose an operation from the following: " << "\n"; cout << "\n"; cout << "\t 1. Convert dense data structure to sparse" << "\n"; cout << "\t 2. Convert sparse data structure to dense" << "\n"; cout << "\t 3. Perform matrix multiplication of 2D arrays: " << "\n"; cout << "\t 4. Compute kronecker products of 2 multidimensional arrays: " << "\n"; cout << "\t 5. Compute kronecker outer products of 2 multidimensional arrays: " << "\n"; cout << "\t 6. Measure time taken for naive sparse Matrix multiplication: " << "\n"; std::cin >> choice; switch (choice) { case 1: case1(); break; case 2: case2(); break; case 3: case3(); break; case 4: case4(); break; case 5: case5(); break; case 6: case6(); break; default: cout << " We're done " << "\n"; return 0; } } while(choice != 0); } void case1() { vector<vector<int>> a(M, vector<int>(N, 0)); cout << "Please enter a 2D array: " << "\n"; for (auto &row : a) { for (auto &col : row) { std::cin >> col; } } vector<SparseMatrixEntry> vs; vs.emplace_back(SparseMatrixEntry(0, 1, a[0][1])); vs.emplace_back(SparseMatrixEntry(1, 0, a[1][0])); vs.emplace_back(SparseMatrixEntry(1, 4, a[1][4])); vs.emplace_back(SparseMatrixEntry(2, 0, a[2][0])); vs.emplace_back(SparseMatrixEntry(2, 1, a[2][1])); vs.emplace_back(SparseMatrixEntry(2, 3, a[2][3])); vs.emplace_back(SparseMatrixEntry(4, 3, a[4][3])); vs.emplace_back(SparseMatrixEntry(4, 4, a[4][4])); std::cout << vs << "\n"; } void case2() { vector<SparseMatrixEntry> d; int i, j, k; for (int ii = 0; ii < 8; ++ii) { cout << "Please enter row position, column position and element value: "; std::cin >> i >> j >> k; d.emplace_back(SparseMatrixEntry(i, j, k)); } // d.emplace_back(SparseMatrixEntry(0, 1, 3)); // d.emplace_back(SparseMatrixEntry(1, 0, 22)); // d.emplace_back(SparseMatrixEntry(1, 4, 17)); // d.emplace_back(SparseMatrixEntry(2, 0, 7)); // d.emplace_back(SparseMatrixEntry(2, 1, 5)); // d.emplace_back(SparseMatrixEntry(2, 3, 1)); // d.emplace_back(SparseMatrixEntry(4, 2, 14)); // d.emplace_back(SparseMatrixEntry(4, 4, 8)); std::cout << d; std::cout << "\n"; std::vector<std::vector<int>> vd(M, std::vector<int>(N, 0)); vd[0][1] = d[0].value; vd[1][0] = d[1].value; vd[1][4] = d[2].value; vd[2][0] = d[3].value; vd[2][1] = d[4].value; vd[2][3] = d[5].value; vd[4][2] = d[6].value; vd[4][4] = d[7].value; std::cout << vd; } void case3() { vector<vector<int>> A(M, vector<int>(N, 0)); vector<vector<int>> B(M, vector<int>(N, 0)); cout << "Please enter a 2D array A: " << "\n"; for (auto &row : A) { for (auto &col : row) { std::cin >> col; } } cout << "Please enter a 2D array B: " << "\n"; for (auto &row : B) { for (auto &col : row) { std::cin >> col; } } // vector<vector<Value>> A{{{0, 3, 0, 0, 0}, {22, 0, 0, 0, 17}, // {7, 5, 0, 1, 0}, {0, 0, 0, 0, 0}, {0, 0, 14, 0, 8}}}; // // vector<vector<Value>> B{{{0, 3, 0, 0, 0}, {0, 0, 0, 0, 17}, // {7, 5, 0, 1, 0}, {0, 0, 0, 0, 0}, {0, 0, 14, 0, 8}}}; cout << "The multiplication result from SparMul() is: " << "\n"; vector<vector<Value>> C = SparseMul(A, B); std::cout << C; cout << "The multiplication result from MatMultiply() is: " << "\n"; Matrix D = MatMultiply(A, B); std::cout << D; } void case4() { Matrix m1(M, vector<int>(N, 0)); Matrix m2(M, vector<int>(N, 0)); cout << "Please enter the first matrix for KroneckersProduct: " << "\n"; for (auto &row : m1) { for (auto &col : row) { std::cin >> col; } } cout << "Please enter the second matrix for KroneckersProduct: " << "\n"; for (auto &row : m2) { for (auto &col : row) { std::cin >> col; } } Matrix v(KroneckersProduct(m1, m2)); std::cout << v; } void case5() { Matrix m1(M, vector<int>(N, 0)); Matrix m2(M, vector<int>(N, 0)); cout << "Please enter the first matrix for KroneckersOuterProduct: " << "\n"; for (auto &row : m1) { for (auto &col : row) { std::cin >> col; } } cout << "Please enter the second matrix for KroneckersOuterProduct: " << "\n"; for (auto &row : m2) { for (auto &col : row)) { std::cin >> col; } } Tensor m(KroneckersOuterProduct(m1, m2)); nested_print(std::span(m)); std::random_device rd; std::mt19937 gen(rd()); std::uniform_real_distribution<> dis(1.0, 10.0); vector<vector<double>> Matrix(5, vector<double>(7, 0)); std::ofstream file("matrix.txt"); for (auto &row : Matrix) { for (auto &col : row) { col = dis(gen); file << std::setw(4) << col; } file << '\n'; } } void case6() { matrix<int, double> mtx(M, N, 0); matrix<int, double> mty(M, N, 0); cout << "Please enter element of sparse matrix A" << "\n"; for (int i = 0; i != mtx.num_rows(); ++i) { for (int j = 0; j != mtx.num_cols(); ++j) { std::cin >> mtx(i, j) ; } } cout << "Please enter element of sparse matrix B" << "\n"; for (int i = 0; i != mty.num_rows(); ++i) { for (int j = 0; j != mty.num_cols(); ++j) { std::cin >> mty(i, j) ; } } Timer t; matrix<int, double> mtz = mtx * mty; std::cerr << "Measure time taken for printing naive Matrix multiplication (fmt): " << "\n"; Timer tt; for (int i = 0; i != mtz.num_rows(); ++i) { for (int j = 0; j != mtz.num_cols(); ++j) { std::cout << mtz(i, j) << " "; } std::cout << "\n"; } } //g++-10 -std=c++2a -o sparse testlib.cpp SparseTensor/src/SparseTensor.cpp -lfmt