Matrix multiplication $A^t A$ appears as intermediate operation during the solution of a wide set of problems. In this paper, we propose a new cache-oblivious algorithm for the $A^t A$ multiplication. Our algorithm, A$scriptstyle mathsf{T}$A, calls classical Strassens algorithm as sub-routine, decreasing the computational cost %(expressed in number of performed products) of the conventional $A^t A$ multiplication to $frac{2}{7}n^{log_2 7}$. It works for generic rectangular matrices and exploits the peculiar symmetry of the resulting product matrix for sparing memory. We used the MPI paradigm to implement A$scriptstyle mathsf{T}$A in parallel, and we tested its performances on a small subset of nodes of the Galileo cluster. Experiments highlight good scalability and speed-up, also thanks to minimal number of exchanged messages in the designed communication system. Parallel overhead and inherently sequential time fraction are negligible in the tested configurations.
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