Numerical efficiency of CUDA based parallel programming for dynamic analysis of multi-body systems with multi-joints and multi-force elements

The graphic processor unit (GPU) is an ideal solution to problems involving parallel data computations. A serial CPU-based program of dynamic analysis for multi-body systems is rebuilt as a parallel program that uses the GPU’s advantages. We developed an analysis code named GMAP to investigate how the dynamic analysis algorithm of multi-body systems is implemented in the GPU parallel programming. The numerical accuracy of GMAP is compared with the commercial program MSC/ADAMS. The numerical efficiency of GMAP is compared with the sequential CPU-based program. Multiple pendulums with bodies and joints and the net-shape system with bodies and spring-dampers are employed for computer simulations. The simulation results indicate that the accuracy of GMAP’s solution is the same as that of ADAMS. In the net type system that has 2370 spring-dampers, GMAP indicates an improved efficiency of about 566.7 seconds (24.7% improvement). It is noted that the larger the size of the system, the better the time efficiency.