Volume 26 (2018) Pages 237-246
Diverse simulations on centralized high performance computers are the driving force behind innovation in nearly all fields. Higher resolution and real-time interactions of users are expected to reveal valuable phenomena by providing more precise details and efficient dynamic steering inside simulations. If simulations are performed at a centralized server, such as supercomputer or cloud system, it is difficult to satisfy the requirements of both real-time interaction and high-resolution for many of those user's domain of interest (DoI). To solve this problem, we utilize distributed regional servers closer to users to perform simulations for each independent DoI region. However, this may introduce inaccuracies in the boundary condition for each DoI region. In order to improve the boundary conditions for better regional simulations, the servers must cooperate to exchange necessary information. For this reason, this paper proposes a general purpose framework named Silk Road, to help application users realize a distributed collaborative simulation which utilizes regional servers to perform high-resolution simulation with low network delay, with help from exchanging boundary conditions through collaborations with each other via a central server which performs a low-resolution but wider area simulation to couple the regional simulations to propagate the higher resolution simulation results. The most notable feature of Silk Road Framework is the bi-directional refinement of on-going simulation by exchanging an adequate amount of simulation results occasionally without inducing unacceptable network delays. Through a case study, with a 2D diffusion simulation, we show the framework can achieve the distributed collaborative simulation and our model can help refine simulations on both the regional and central server side.