We study applications of clustering (in particular the k-center clustering problem) in the design of efficient and practical deterministic algorithms for computing an approximate and the exact arithmetic matrix product of two 0-1 rectangular matrices A and B with clustered rows or columns, respectively. Let \(\lambda _A\) and \(\lambda _B\) denote the minimum maximum radius of a cluster in an \(\ell \) -center clustering of the rows of A and in a k-center clustering of the columns of B,  respectively. In particular, when A and B are square matrices of size \(n\times n\) , we obtain the following results.