Matrix multiplication, a little faster

Strassen's algorithm (1969) was the first sub-cubic matrix multiplication algorithm. Winograd (1971) improved its complexity by a constant factor. Many asymptotic improvements followed. Unfortunately, most of them have done so at the cost of very large, o.en gigantic, hidden constants. Consequently, Strassen-Winograd's O (nlog2⁷) algorithm o.en outperforms other matrix multiplication algorithms for all feasible matrix dimensions. The leading coefficient of Strassen-Winograd's algorithm was believed to be optimal for matrix multiplication algorithms with 2 × 2 base case, due to a lower bound of Probert (1976). Surprisingly, we obtain a faster matrix multiplication algorithm, with the same base case size and asymptotic complexity as Strassen- Winograd's algorithm, but with the coefficient reduced from 6 to 5. To this end, we extend Bodrato's (2010) method for matrix squaring, and transform matrices to an alternative basis. We prove a generalization of Probert's lower bound that holds under change of basis, showing that for matrix multiplication algorithms with a 2×2 base case, the leading coefficient of our algorithm cannot be further reduced, hence optimal. We apply our technique to other Strassenlike algorithms, improving their arithmetic and communication costs by significant constant factors.