Performance Evaluation of two Parallel Programming Paradigms Applied to the Symplectic Integrator Running on COTS PC Cluster

There are two popular parallel programming paradigms available to high performance computing users such as engineering and physics professionals: message passing and distributed shared memory. It is interesting to have a comparative evaluation of these paradigms to choose the most adequate one. In this work, we present a performance comparison of these two programming paradigms using a computational physics problem as a case study. The self-gravitating ring model (Hamiltonian mean field model) for N particles is extensively studied in the literature as a simplified model for long range interacting systems in Physics. We parallelized and evaluated the performance of a simulation that uses the symplectic integrator to model an N particle system. From the obtained results it is possible to observe that message passing implementation of the symplectic integrator presents better results than distributed shared memory implementation.