| dc.description.abstract | Due to the many computational applications of matrix multiplication, research into efficient algorithms for multiplying matrices can lead to widespread improvements of performance. In this thesis, we will first make the reader familiar with a universal measure of the efficiency of an algorithm, its computational complexity. We will then examine the Strassen algorithm, an algorithm that improves on the computational complexity of the conventional method for matrix multiplication. To illustrate the impact of this difference in complexity, we implement and test both algorithms, and compare their runtimes. Our results show that while Strassen’s method improves on the theoretical complexity of matrix multiplication, there are a number of practical considerations that need to be addressed for this to actually result in improvements on runtime. | |
