Strassen's Matrix multiplication
Last updated
Last updated
Given two square matrices A and B of size n x n each, find their multiplication matrix. Naive Method Following is a simple way to multiply two matrices.
Time Complexity of above method is O(N^3).
Divide and Conquer Following is simple Divide and Conquer method to multiply two square matrices. 1) Divide matrices A and B in 4 sub-matrices of size N/2 x N/2 as shown in the below diagram. 2) Calculate following values recursively. ae + bg, af + bh, ce + dg and cf + dh.
In the above method, we do 8 multiplications for matrices of size N/2 x N/2 and 4 additions. Addition of two matrices takes O(N2) time. So the time complexity can be written as
Simple Divide and Conquer also leads to O(N3), can there be a better way? In the above divide and conquer method, the main component for high time complexity is 8 recursive calls.
The idea of Strassen’s method is to reduce the number of recursive calls to 7. Strassen’s method is similar to above simple divide and conquer method in the sense that this method also divide matrices to sub-matrices of size N/2 x N/2 as shown in the above diagram, but in Strassen’s method, the four sub-matrices of result are calculated using following formulae.
Time Complexity of Strassen’s Method Addition and Subtraction of two matrices takes O(N^2) time. So time complexity can be written as
void multiply(int A[][N], int B[][N], int C[][N])
{
for (int i = 0; i < N; i++)
{
for (int j = 0; j < N; j++)
{
C[i][j] = 0;
for (int k = 0; k < N; k++)
{
C[i][j] += A[i][k]*B[k][j];
}
}
}
}
