Design and implementation of a data-driven simulation service system

Computer simulations are widely used in various fields of science and engineering, including computational fluid dynamics. As the demand for the accuracy and quality of simulations grows, the cost of executing simulations itself is also rapidly increasing. However, until now, the reuse of previously obtained simulation results to improve the execution of later simulations has not been much investigated yet. In this paper, we design and implement a simulation service system, which executes requested simulations and returns the result back to the user. More importantly, our simulation service system is data-driven in the sense that the system utilizes previously obtained simulation results to improve the execution of later simulations. Furthermore, our system provides the ability to predict the result of a requested simulation using statistical machine learning techniques on the previous simulation results. This allows the user to roughly estimate the result of her requested simulation without actually executing it. Using our developed system, scientists and engineers can share simulation results and obtain simulation results very quickly without executing simulations redundantly, resulting in a lower overhead of the simulation service system.