Objectives: To review various tools available for simulating Spiking Neural Networks using heterogeneous parallel processing platforms that help to reduce cost, increase the computational speed, and also to document/archive lessons learned. Methods/Statistical Analysis: The computational speed is a continuing challenge for simulating good spiking neural network models. Understanding of the spiking neural networks is significantly simplified by computer simulators like NEST, GeNN, EDLUT, and BRIAN. Findings: Simulation is a handy toolkit of scientists and engineers of all disciplines. NEST, GeNN, EDLUT, and BRIAN simulators help in achieving better performance not in terms of the same kind of processing but with additional particular tasks that require more computational power. BRIAN and EDLUT, which are hybrid simulators, supports both time-driven and event-driven techniques and outperform when compared to other simulators. Application/Improvements: Using BRIAN and EDLUT simulation techniques, we can achieve high performance when compared to other spiking neural simulation techniques.

Keywords: NEST; GENN; EDLUT; BRIAN