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We present COPSIM a parallel implementation of standard integer multiplication for the distributed memory setting, and COPK a parallel implementation of Karatsuba's fast integer multiplication algorithm for a distributed memory setting. When using $\mathcal{P}$ processors, each equipped with a local non-shared memory, to compute the product of tho $n$-digits integer numbers, under mild conditions, our algorithms achieve optimal speedup of the computational time. That is, $\mathcal{O}\left(n^2/\mathcal{P}\right)$ for COPSIM, and $\mathcal{O}\left(n^{\log_2 3}/\mathcal{P}\right)$ for COPK. The total amount of memory required across the processors is $\mathcal{O}\left(n\right)$, that is, within a constant factor of the minimum space required to store the input values. We rigorously analyze the Input/Output (I/O) cost of the proposed algorithms. We show that their bandwidth cost (i.e., the number of memory words sent or received by at least one processors) matches asymptotically corresponding known I/O lower bounds, and their latency (i.e., the number of messages sent or received in the algorithm's critical execution path) is asymptotically within a multiplicative factor $\mathcal{O}\left(\log^2_2 \mathcal{P}\right)$ of the corresponding known I/O lower bounds. Hence, our algorithms are asymptotically optimal with respect to the bandwidth cost and almost asymptotically optimal with respect to the latency cost.