Cooperative spatial exploration in initially unknown surroundings is a common embodied task in various applications and requires satisfactory coordination among the agents. Unlike many other research questions, there is a lack of simulation platforms for the cooperative exploration problem to perform and statistically evaluate different methods before they are deployed in practical scenarios. To this end, this paper designs a simulation framework to run different models, which features efficient event scheduling and data sharing. On top of such a framework, we propose and implement two different cooperative exploration strategies, i.e., the synchronous and asynchronous ones. While the coordination in the former approach is conducted after gathering the perceptive information from all agents in each round, the latter enables an ad-hoc coordination. Accordingly, they exploit different principles for assigning target points for the agents. Extensive experiments on different types of environments and settings not only validate the scheduling efficiency of our simulation engine, but also demonstrate the respective advantages of the two strategies on different metrics.