Skip to content

leannejdong/SparseTensor

BranchesTags

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

17 Commits
include
include
 
 
src
src
 
 
.gitignore
.gitignore
 
 
CMakeLists.txt
CMakeLists.txt
 
 
Doxyfile
Doxyfile
 
 
LICENSE
LICENSE
 
 
README.md
README.md
 
 

Repository files navigation

Naïve sparse matrix/tensor library

(Work in Progress)

Dependency

  • GCC10

  • GNU Build System (a.k.a. Make)

  • C++20

  • fast open-source formatting library {fmt}

(Doxygen was used to generate documentation, can be safely ignored)

Instruction

  • Copy codes below, save it in a file testlib.cpp in 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/*.d

execute make from terminal to build. Use make clean to clean auxiliary files (if needed).

  • To run, execute ./sparse or ./sparse >file.txt 2>&1 to redirect all terminal output to a file. (Demo 1) Or ./sparse 2>&1 | tee file.txt to redirect all terminal output to a file (Demo 2)

Demo 1

#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

Demo 2 (Read user inputs)

#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

About

No description, website, or topics provided.

Resources

Readme

License

BSD-2-Clause license
Activity

Stars

1 star

Watchers

2 watching

Forks

2 forks
Report repository

Releases

No releases published

Packages

No packages published

Languages