Cross Teaching Parallelism and Ray Tracing: A Project-based Approach to Teaching Applied Parallel Computing

Massively parallel Graphics Processing Unit (GPU) hardware has become increasingly powerful, available and affordable. Software tools have also advanced to the point that programmers can write general purpose parallel programs that take advantage of the large number of compute cores available in the hardware. With literally hundreds of compute cores available on a single device, program performance can increase by orders of magnitude. We believe that introducing students to the concepts of parallel programming for massively parallel hardware is of increasing importance in an undergraduate computer science curriculum. Furthermore, we believe that students learn best when given projects that reflect real problems in computer science. This paper describes the experience of integrating two undergraduate computer science courses to enhance student learning in parallel computing concepts. In this cross teaching experience we structured the integration of the courses such that students studying parallel computing worked with students studying advanced rendering for approximately 30% of the quarter long courses. Working in teams on a joint project, both groups of students were able to see the application of parallelization to an existing software project with both the benefits and complications exposed early in the curriculum of both courses. Motivating projects and performance gains are discussed, as well as student survey data on the effectiveness of the learning outcomes. Both performance and survey data indicate a positive gain from the cross teaching experience

Topological Noise Removal

Meshes obtained from laser scanner data often contain topological noise due to inaccuracies in the scanning and merging process. This topological noise complicates subsequent operations such as remeshing, parameterization and smoothing. We introduce an approach that removes unnecessary nontrivial topology from meshes. Using a local wave front traversal, we discover the local topolo-gies of the mesh and identify features such as small tunnels. We then identify non-separating cuts along which we cut and seal the mesh, reducing the genus and thus the topological complexity of the mesh

Direct Extraction of Normal Mapped Meshes from Volume Data

We describe a method of directly extracting a simplified contour surface along with detailed normal maps from volume data in one fast and integrated process. A robust dual contouring algorithm is used for efficiently extracting a high-quality crack-free simplified surface from volume data. As each polygon is generated, the normal map is simultaneously generated. An underlying octree data structure reduces the search space required for high to low resolution surface normal mapping. The process quickly yields simplified meshes fitted with normal maps that accurately resemble their complex equivalents

Locating the source of topological error in reconstructed 3D models

Although range scanning technology has offered great improvements to digital model creation in recent years, it has also introduced some new concerns. Specifically, recent work shows that topological errors such as tiny handles can significantly lower the overall quality of range-scanned models for down-stream applications (such as simplification and parameterization). In this paper we present our investigation into the source of this topological error in the range scanning process, and our methods to alleviate the error. We concentrated our investigation of the scanning process on: (1) signal noise or calibration error in the laser scanner (resulting in bad data points) and (2) error during the model reconstruction phase. We found that by modifying the surface reconstruction phase of the range scanning process, we were able to reduce the amount of topological noise in the resulting 3D model by up to 60 percent

Interactive Thin Shells – A Model Interface for the Analysis of Physically-Based Animation

Realism has always been a goal in computer graphics. However, the algorithms involved in mimicking the physical world are often complex, abstract, and sensitive to changes in experimental parameters. We present an interface to a physically-based algorithm, a thin shell animation, which focuses on visualization, experimentation, and control. Through the use of dynamic surface coloring, abstract visual cues, robust user interaction, and full control over the algorithm parameters, our system facilitates experimentation and the process of discovery. The system is targeted at enhancing the user’s learning experience by clarifying interactions between various components of many physically-based animations

Discrete Shells Origami

We introduce a way of simulating the creation of simple Origami (paper folding). The Origami is created in a thin shell simulation that realistically models the behavior and physical properties of paper. We demonstrate how to fold and crease the simulated paper wherever the user desires. This work employs cutting-edge advances in the field of discrete shell modeling to meet the challenge of simulating Origami. We found that the discrete shell model is capable of creating simple Origami that does not involve paper to paper collisions. For more advanced origami, however, some kind of collision detection and resolution scheme is required. Further research is necessary to implement collision handling while maintaining a practical simulation speed

Removing Excess Topology from Isosurfaces

Many high-resolution surfaces are created through isosurface extraction from volumetric representations, obtained by 3D photography, CT, or MRI. Noise inherent in the acquisition process can lead to geometrical and topological errors. Reducing geometrical errors during reconstruction is well studied. However, isosurfaces often contain many topological errors in the form of tiny handles. These nearly invisible artifacts hinder subsequent operations like mesh simplification, remeshing, and parametrization. In this article we present a practical method for removing handles in an isosurface. Our algorithm makes an axis-aligned sweep through the volume to locate handles, compute their sizes, and selectively remove them. The algorithm is designed to facilitate out-of-core execution. It finds the handles by incrementally constructing and analyzing a Reeb graph. The size of a handle is measured by a short nonseparating cycle. Handles are removed robustly by modifying the volume rather than attempting “mesh surgery.” Finally, the volumetric modifications are spatially localized to preserve geometrical detail. We demonstrate topology simplification on several complex models, and show its benefits for subsequent surface processing