In the field of computational neuroscience, the parallel simulation of largescale neuronal networks plays a very important role in exploring and revealing the information processing mechanism of the brain. In order to accelerate the largescale neuronal network simulation,an efficient parallel neuronal network algorithm based on synaptic neurotransmitterreceptor ion channel kinetic characteristics is proposed. By analyzing the information transmission mechanisms and the neurotransmitterreceptor ion channel kinetic characteristics of the chemical synapse, we propose an idea of the separation of presynaptic neurotransmitter computing from postsynaptic receptor computing. The new idea enhances the independence of the two concentration calculation: neurotransmitter emitted by presynaptic neurons, and the bound postsynaptic receptors.During each synaptic current computing, the new idea reduces the coupling degree of the presynaptic neuron and the postsynaptic neuron.Based on the new idea, we design a parallel algorithm for parallel neuronal network simulation based on synaptic ion channel kinetic.Simulation results show that the algorithm is efficient.