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Abstract
The paper presents first the formal semantics of a parallel formalism inspired by biological cells, and then provides a faithful parallel implementation of this computational model using a known distributed computing middleware and taking care of various synchronization issues. Synchronization is achieved using barriers and preconditions; both refer to the fact that a membrane can apply its rules only after it has received signals from the other related membranes. A scalable parallel implementation is developed by using the MapReduce paradigm in GridGain which allows the splitting of a task into multiple subtasks, the parallel execution of these subtasks in parallel and the aggregation of the partial results into a single, final result. This implementation is appropriate for the description of this bio-inspired parallel model, a model which is computationally equivalent to Turing machines and able to provide polynomial solutions to NP-complete problems.
