The art of deception: Adaptive precision reduction for area efficient physics acceleration

Thomas Y. Yeh, Petros Faloutsos, Milos Ercegovac, Sanjay Patel, Glenn Reinman

Abstract: Physics-based animation has enormous potential to improve the realism of interactive entertainment through dynamic, immersive content creation. Despite the massively parallel nature of physics simulation, fully exploiting this parallelism to reach interactive frame rates will require significant area to place the large number of cores. Fortunately, interactive entertainment requires believability rather than accuracy. Recent work shows that real-time physics has a remarkable tolerance for reduced precision of the significand in floating-point (FP) operations. In this paper, we describe an architecture with a hierarchical floating-point unit (FPU) that leverages dynamic precision reduction to enable efficient FPU sharing among multiple cores. This sharing reduces the area required by these cores, thereby allowing more cores to be packed into a given area and exploiting more parallelism.