The use of a distributed memory message-passing multicomputer for dynamic simulation of chemical processes is investigated. The computational speed-up expected from the parallel implementation of the modular integration approach depends crucially on appropriate partitioning of the overall system into smaller sub-systems (modules), and the need for coordination and synchronization of module integrations to account for the interaction effects among the sub-systems. In this paper, a coordination algorithm based on a dynamic block Jacobi-like iteration is employed. Sufficient conditions for the finite-time convergence of the iterative solution scheme are established. These conditions are shown to be very useful in quantifying the convergence rate that can be used as a basis for adjusting the integration time horizon and selection of the best process system partitioning strategy. Timing results from simulation of the dynamics of a multicomponent distillation column on a distributed memory message-passing multicomputer demonstrate the potential of the proposed implementation. The results suggest that the execution time of modular dynamic process simulation can be reduced very significantly by distributing the module integrations onto several computing nodes communicating via high-performance communication networks.