In this paper has an objective to study parallel processing method for the efficient analysis of multi-body vehicle model based on subsystem synthesis method. In order to improve the calculation efficiency, parallel processing method was applied 6x6 unmanned vehicle robot which is a vehicle model based on subsystem synthesis method. Subsystem synthesis method is a method that can efficiently analyze equations of motion in the entire system, divided into base body and each subsystems.
Since subsystem synthesis method analyzes the system into base body and several subsystems, it is suitable for parallel processing. It also has a merit that a different integrator can be applied to each subsystem. In this paper, applied parallel processing method was been applied to a vehicle model based on the subsystem synthesis method with different integrators(explicit integration method, implicit integration method, explicit-implicit integration method).
For parallel program implementation, OpenMP API(Application Program Interface) for a shared memory multi-core CPU was utilized. Three different parallel implementations were applied, to examine the performance of parallel processing. In the first, parallel processing was applied only to identified parallel regions in the subsystem synthesis method within the integration time loop. In the second, parallel processing was applied from the beginning of the program in order to avoid overhead due to the creation of parallel threads in every time step. The 3rd implementation was basically the same as the 2nd one, except that unnecessary data synchronization overhead was removed.
In order to investigate the performance of the proposed parallel processing, parallel programs with three different implementations were created for a 6x6 unmanned robot vehicle model. Rough terrain run simulations were carried out. Performance of the 1st and 2nd implementation methods were worse than that of serial program. When parallel processing with proper treatment of overheads was used, in the 3rd implementation, the CPU time results showed a three times increase in speed was achieved from parallel processing, compared with serial computation.