Abstract: Interactive entertainment (IE) applications are rapidly gaining significance from both technical and economical point of views. Future IE applications will feature on-the-fly content creation with large number of interacting objects, intelligent agents, and high-definition rendering. Application designers must provide at least 30 graphical frames per second to provide the illusion of visual continuity. While IE's real-time constraint necessitates a tremendous amount of performance, almost no academic attention in the architecture community has been directed at quantifying the needs of this emerging workload. In this dissertation, we focus on the acceleration of one core component of this emerging workload, namely real-time physics simulation or physics based animation (PBA). Our holistic approach to acceleration spans benchmark creation, workload characterization, architectural acceleration, algorithmic acceleration, and architectural exploitation of algorithmic properties. To represent this emerging workload, we developed PhysicsBench, a set of benchmarks to capture the complexity and scale of PBA in IE applications. Using the PhysicsBench suite, we characterized the workload to identify its key differentiating factors. Based on the characterization, we propose ParallAX, an architecture to sustain interactive frame rates for real-time physics. The ParallAX architecture is a heterogeneous chip-multiprocessor that features aggressive coarse-grain cores and area-efficient fine-grain cores. Scaling the number of active cores per chip increases the load on the lowest-level cache. To alleviate cache thrashing, we propose the Performance Driven Adaptive Sharing (PDAS) cache design. PDAS is a scalable, multiported NUCA that dynamically allocates its distributed cache resources through an intelligent, realizable on-line partitioning strategy. In addition to parallelism, the human perception error tolerance can also be leveraged for performance in PBA. Using prior studies of simpler scenes as a starting point, we extrapolate a methodology for evaluating the tolerable error of complex scenes. Leveraging the findings from these studies, we propose architectural techniques to exploit algorithmic properties of PBA, namely perceptual error tolerance and the notion of object-pairs. To summarize, this dissertation is an in-depth study on the acceleration of realtime physics simulation. Given physics' similarity to other software components, our proposed methodologies and techniques can be applied to many areas within the IE space.