The numerical simulation of highly complex biomolecular systems such as DNAs, RNAs, and proteins become intractable as the size and fidelity of these systems increase. Herein, efficient techniques to accelerate multibody-based coarsegrained simulations of such systems are presented. First, an adaptive coarse-graining framework is explained which is capable of determining when and where the system model needs to change to achieve an optimal combination of speed and accuracy. The metrics to guide these on-the-fly instantaneous model adjustments and the issues associated with post-transition system's states are addressed in this book chapter. Due to its highly modular and parallel nature, the Generalized Divide-and- Conquer Algorithm (GDCA) forms the bases for a suite of dynamics simulation tools used in this work. For completeness, the fundamental aspects of the GDCA are presented herein. Finally, a novel method for the efficient and accurate approximation of far-field force and moment terms are developed. This aspect is key to the success of any large molecular simulation since more than 90 % of the computational load in such simulations is associated with pairwise force calculations. The presented approximations are efficient, accurate, and highly compatible with multibody-based coarse-grained models.