inheritance真的不影响性能吗？

Question

I have found on the internet ( here and here ), that the inheritance doesn't affect the performance of the class. I have become curious about that as I have been writing a matrices module for a render engine, and the speed of this module is very important for me.

After I have written:

• Base: general matrix class
• Derived from the base: square implementation
• Derived from derived: 3-dim and 4-dim implementations of the square matrix

I decided to test them and faced performance issues with instantiation

And so the main questions are:

1. What's the reason of these performance issues in my case and why may they happen in general?
2. Should I forget about inheritance in such cases?

This is how these classes look like in general:

template <class t>
class Matrix
{
protected:
    union {
        struct
        {
            unsigned int w, h;
        };
        struct
        {
            unsigned int n, m;
        };
    };

    /** Changes flow of accessing `v` array members */
    bool transposed;

    /** Matrix values array */
    t* v;

public:
    ~Matrix() {
        delete[] v;
    };
    Matrix() : v{}, transposed(false) {};

    // Copy
    Matrix(const Matrix<t>& m) : w(m.w), h(m.h), transposed(m.transposed) {
        v = new t[m.w * m.h];
        for (unsigned i = 0; i < m.g_length(); i++)
           v[i] = m.g_v()[i];
    };

    // Constructor from array
    Matrix(unsigned _w, unsigned _h, t _v[], bool _transposed = false) : w(_w), h(_h), transposed(_transposed) {
       v = new t[_w * _h];
       for (unsigned i = 0; i < _w * _h; i++)
           v[i] = _v[i];
    };

    /** Gets matrix array */
    inline t* g_v() const { return v; }
    /** Gets matrix values array size */
    inline unsigned g_length() const { return w * h; }

    // Other constructors, operators, and methods.
}



template<class t>
class SquareMatrix : public Matrix<t> {
public:
    SquareMatrix() : Matrix<t>() {};
    SquareMatrix(const Matrix<t>& m) : Matrix<t>(m) {};

    SquareMatrix(unsigned _s, t _v[], bool _transpose) : Matrix<t>(_s, _s, _v, _transpose) {};
    // Others...
}

template<class t>
class Matrix4 : public SquareMatrix<t> {
public:
    Matrix4() : SquareMatrix<t>() {};
    Matrix4(const Matrix<t>& m) : SquareMatrix<t>(m) {}

    Matrix4(t _v[16], bool _transpose) : SquareMatrix<t>(4, _v, _transpose) {};
    // Others...
}

To conduct tests I used this

void test(std::ofstream& f, char delim, std::function<void(void)> callback) {
    auto t1 = std::chrono::high_resolution_clock::now();
    callback();
    auto t2 = std::chrono::high_resolution_clock::now();
    f << std::chrono::duration_cast<std::chrono::microseconds>(t2 - t1).count() << delim;
    //std::cout << "test took " << std::chrono::duration_cast<std::chrono::microseconds>(t2 - t1).count() << " microseconds\n";
}

Performance problems

With single class initialization, there're no problems - it goes under 5 microseconds almost every time for every class. But then I decided to scale up the number of initializations and their several troubles occurred

I ran every test 100 times, with arrays of length 500

1. Class initialization with the default constructor

Raw results

I just tested the initialization of arrays

The results were (avg time in microseconds):

• Matrix 25.19
• SquareMatrix 40.37 (37.60% loss)
• Matrix4 58.06 (30.47% loss from SquareMatrix)

And here we can already see a huge difference

Here's the code

int main(int argc, char** argv)
{
    std::ofstream f("test.csv");
    f << "Matrix\t" << "SquareMatrix\t" << "Matrix4\n";

    for (int k = 0; k < 100; k++) {
        test(f, '\t', []() {
            Matrix<long double>* a = new Matrix<long double>[500];
            });

        test(f, '\t', []() {
            SquareMatrix<long double>* a = new SquareMatrix<long double>[500];
            });

        test(f, '\n', []() {
            Matrix4<long double>* a = new Matrix4<long double>[500];
            });
    }

    f.close();

    return 0;
}

2. Class initialization with default constructor and filling

Raw results

Tested the initialization of arrays of class instances and filling them after with custom matrices

The results (avg time in microseconds):

• Matrix 402.8
• SquareMatrix 475 (15.20% loss)
• Matrix4 593.86 (20.01% loss from SquareMatrix)

Code

int main(int argc, char** argv)
{
    long double arr[16] = {
       1, 2, 3, 4,
       5, 6, 7, 8,
       9, 10, 11, 12,
       13, 14,15,16
    };

    std::ofstream f("test.csv");
    f << "Matrix\t" << "SquareMatrix\t" << "Matrix4\n";

    for (int k = 0; k < 100; k++) {
        test(f, '\t', [&arr]() {
            Matrix<long double>* a = new Matrix<long double>[500];
            for (int i = 0; i < 500; i++) 
                a[i] = Matrix<long double>(4, 4, arr);
            });

        test(f, '\t', [&arr]() {
            SquareMatrix<long double>* a = new SquareMatrix<long double>[500];
            for (int i = 0; i < 500; i++) 
                a[i] = SquareMatrix<long double>(4, arr);
            });

        test(f, '\n', [&arr]() {
            Matrix4<long double>* a = new Matrix4<long double>[500];
            for (int i = 0; i < 500; i++) 
                a[i] = Matrix4<long double>(arr);
            });
    }

    f.close();

    return 0;
}

3. Filling vector with class instances

Raw results

Pushed back custom matrices to vector

The results (avg time in microseconds):

• Matrix 4498.1
• SquareMatrix 4693.93 (4.17% loss)
• Matrix4 4960.12 (5.37% loss from its SquareMatrix)

Code

int main(int argc, char** argv)
{
    long double arr[16] = {
       1, 2, 3, 4,
       5, 6, 7, 8,
       9, 10, 11, 12,
       13, 14,15,16
    };

    std::ofstream f("test.csv");
    f << "Matrix\t" << "SquareMatrix\t" << "Matrix4\n";

    for (int k = 0; k < 100; k++) {
        test(f, '\t', [&arr]() {
            std::vector<Matrix<long double>> a = std::vector<Matrix<long double>>();
            for (int i = 0; i < 500; i++)
                a.push_back(Matrix<long double>(4, 4, arr));
            });

        test(f, '\t', [&arr]() {
            std::vector<SquareMatrix<long double>> a = std::vector<SquareMatrix<long double>>();
            for (int i = 0; i < 500; i++)
                a.push_back(SquareMatrix<long double>(4, arr));
            });

        test(f, '\n', [&arr]() {
            std::vector<Matrix4<long double>> a = std::vector<Matrix4<long double>>();
            for (int i = 0; i < 500; i++)
                a.push_back(Matrix4<long double>(arr));
            });
    }

    f.close();

    return 0;
}

If you need all the source code, you can look here into matrix.h and matrix.cpp

Answer 1

Does inheritance really not affect performance?

Yes. Inheritance won't affect runtime performance as long as virtual method isn't involved. (Cuz only then will you have to deduce the type at runtime and call corresponding virtual method override). In fact, if you have a sight into lower details, you will know that c++ inheritance is mostly just static things, that is, done at compilation time.

What's the reason of these performance issues in my case and why may they happen in general?

It seems these work well when optimization is enabled?

Should I forget about inheritance in such cases?

The only thing you need to do in such performance-sensitive cases is to avoid virtual method.

Something not related to this question. I have read your code. Perhaps it will be better to implement your templates in header file?