Abstract
P systems have been proven to be useful as modeling tools in many fields, such as Systems Biology and Ecological Modeling. For such applications, the acceleration of P system simulation is often desired, given the computational needs derived from these kinds of models. One promising solution is to implement the inherent parallelism of P systems on platforms with parallel architectures. In this respect, GPU computing proved to be an alternative to more classic approaches in Parallel Computing. It provides a low cost, and a manycore platform with a high level of parallelism. The GPU has been already employed to speedup the simulation of P systems. In this paper, we look over the available parallel P systems simulators on the GPU, with special emphasis on those included in the PMCGPU project, and analyze some useful guidelines for future implementations and developments.