As multi-core processor systems become more and more widespread, the demand for efficient parallel algorithms also propagates into the field of computer graphics. This is especially true for physically-based simulation, which is notorious for expensive numerical methods. In this work, we explore possibilities for accelerating physically-based simulation algorithms on multi-core architectures. Two components of physically-based simulation represent a great potential for bottlenecks in parallelisation: implicit time integration and collision handling. From the parallelisation point of view these two components are substantially different. Implicit time integration can be treated efficiently using static problem decomposition. The linear system arising in this context is solved using a data-parallel preconditioned conjugate gradient algorithm. The collision handling stage, however, requires a different approach, due to its dynamic structure. This stage is handled using multi-threaded programming with fully dynamic task decomposition. In particular, we propose a new task splitting approach based on a reasonable estimation of work, which analyses previous simulation steps. Altogether, the combination of different parallelisation techniques leads to a concise and yet versatile framework for highly efficient physical simulation.