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Strassen's matrix multiplication (MM) has benefits with respect to any (highly tuned) implementations of MM because Strassen's reduces the total number of operations. Strassen achieved this operation reduction by replacing computationally expensive MMs with matrix additions (MAs).
Explanation: Strassen's matrix multiplication algorithm follows divide and conquer technique. In this algorithm the input matrices are divided into n/2 x n/2 sub matrices and then the recurrence relation is applied.
Matrix Chain Multiplication is one of the optimization problem which is widely used in graph algorithms, signal processing and network industry [1–4]. We can have several ways to multiply the given number of matrices because the matrix multiplication is associative.
In this context, using Strassen's Matrix multiplication algorithm, the time consumption can be improved a little bit. Strassen's Matrix multiplication can be performed only on square matrices where n is a power of 2. Order of both of the matrices are n × n.
Strassen's algorithm for matrix multiplication just gives a marginal improvement over the conventional O(N^3) algorithm. It has higher constant factors and is much harder to implement. Given these shortcomings, is strassens algorithm actually useful and is it implemented in any library for matrix multiplication? Moreover, how is matrix multiplication implemented in libraries?
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