Real-time rendering of massive 3D models has been recognized as a challenging task due to the limited computational power and memory available in a workstation. Most existing acceleration techniques, such as mesh simplification algorithms with hierarchical data structures, suffer from the nature of sequential executions. As data complexity increases due to the fundamental advances in modeling and simulation technologies, 3D models become complex and require gigabytes in storage. Consequently, visualizing such large datasets becomes a computationally intensive process where sequential solutions are unable to satisfy the demands of real-time rendering. Recently, the Graphics Processing Unit (GPU) has been praised as a massively parallel architecture not only for its significant improvements in performance but also because of its programmability for general-purpose computation. Today's GPUs allow researchers to solve problems by delivering fine-grained parallel implementations. In this dissertation, I concentrate on the design of parallel algorithms for real-time rendering of massive 3D polygonal models towards modern GPU architectures. As a result, the delivered rendering system supports high-performance visualization of 3D models composed of hundreds of millions of polygons on a single commodity workstation. / Ph. D.