high performance computing on graphics processing units: hgpu.org

At its most basic, object-space edge detection iterates through all polygonal edges in each mesh to find those edges that satisfy one or more edge tests. Those that do are expanded and rendered, while the remainder are ignored. These 3D edges, and their resulting accuracy and customizability, set objectspace methods apart from all other categories of edge detection. The speed and memory limitations of iterating through all polygonal edges in each mesh each frame has inspired optimization research. In this paper, we explore methods to calculate object-space edges utilizing programmable GPU technologies, including OpenCL. The OpenCL methods explored allow for a significant reduction in calculation quantity. Some also provide a reduction in rendering artifacts and memory usage over previous GPU techniques. Unfortunately, most uses of OpenCL for edge detection results in slower performance than shader-based techniques, though variations and optimizations may reduce this disadvantage in the future.