Emilio J. Padrón

Efficient parallel implementations for surface subdivision

Achieving an efficient surface subdivision is an important issue today in computer graphics, geometric modeling, and scientific visualization. In this paper we present two parallel versions of the Modified Butterfly algorithm. Both versions are based on a coarse-grain approach, that is, the original mesh is subdivided into small groups and each processor performs the triangles subdivision for a set of groups of the mesh. First approach sorts the groups in decreasing order of number of triangles per group, and then the sorted groups are cyclically distributed on the processors in order to achieve a good load distribution. In the second parallel version the processors can dynamically balance the work load by passing groups from heavier loaded processors to lighter ones, achieving in that way a better load balance. Finally, we evaluate the algorithms on two different systems: a SGI Origin 2000 and a Sun cluster. Good performances in terms of speedup have been obtained using both static and dynamic parallel implementations.

Progressive radiosity method on clusters using a new clipping algorithm

Global illumination simulation is highly critical for realistic image synthesis; without it, the rendered images look flat and synthetic. The main problem is that the simulation for large scenes is a high time-consuming process. In this paper, we present a uniform partitioning method in order to split the scene domain into a set of disjoint subspaces which are distributed among the processors of a distributed memory system. Since polygons partially inside several subspaces have to be clipped, we have developed a new clipping algorithm to manage this situation. Memory and communication requirements have been minimised in the parallel implementation. Finally, in order to evaluate the proposed method, we have used a progressive radiosity algorithm, running on two different PC clusters with modern processors and network technologies as a testbed. Good results in terms of speedup have been obtained.

Hardware Oriented Algorithms for Rendering Order-Independent Transparency

The demand for high quality and speed in graphical representations of 3D scenes is continuously increasing. An important aspect of visual realism is real-time processing of transparent objects. In order to provide a realistic solution to be considered for future graphics cards, proposed extensions to the hardware need to be small. In this paper, we propose two new hardware oriented proposals for computing order independent transparency for any number of layers. The first proposal is based on the precomputation of the contribution factor of each element to the final colour of the pixel. This permits the evaluation of the transparent objects without requiring their previous sorting. The second proposal is based on the utilization of a pre-sorting stage so that the transparent objects are organized in a back to front order. In both proposals, time requirements are reduced with respect to previous solutions.

Interactive rendering of NURBS surfaces

NURBS (Non-uniform rational B-splines) surfaces are one of the most useful primitives employed for high quality modeling in CAD/CAM tools and graphics software. Since direct evaluation of NURBS surfaces on the GPU is a highly complex task, the usual approach for rendering NURBS is to perform the conversion into Bezier surfaces on the CPU, and then evaluate and tessellate them on the GPU. In this paper we present a new proposal for rendering NURBS surfaces directly on the GPU in order to achieve interactive and real-time rendering. Our proposal, Rendering Pipeline for NURBS Surfaces (RPNS), is based on a new primitive KSQuad that uses a regular and flexible processing of NURBS surfaces, while maintaining their main geometric properties to achieve real-time rendering. RPNS performs an efficient adaptive discretization to fine tune the density of primitives needed to avoid cracks and holes in the final image, applying an efficient non-recursive evaluation of the basis function on the GPU. An implementation of RPNS using current GPUs is presented, achieving real-time rendering rates of complex parametric models. Our experimental tests show a performance several orders of magnitude higher than traditional approximations based on NURBS to Bezier conversion

A Hierarchical Radiosity Method with Scene Distribution

Nowadays, one of the most active areas of research in computer graphics is focused on improving the performance of global illumination methods. In this paper we present a new parallel method for hierarchical radiosity computation. Contrary to usual solutions in the literature our approach carries out an effective partitioning and distribution of the input geometry among the processors. Thus, the memory constraint is reduced when processing large scenes. The method presented in this paper also introduces a multi-thread scheduling to improve interaction between processors. This solution replaces the polling strategy usually used in parallel computing, when several independent tasks need to establish asynchronous communication. The great flexibility of our parallel implementation has been demonstrated by the good results achieved on a testbed with different computing systems and test scenes

Efficient Culling Techniques for Interactive Deformable NURBS Surfaces on GPU

NURBS (Non-uniform rational B-splines) surfaces are the standard freeform representation in Computer-Aided Design (CAD) applications. Rendering NURBS surfaces accurately while they are interactively manipulated and deformed is a challenging task. In order to achieve it, the elimination from pipeline in early stages of back-facing surfaces or surface pieces is a key advantage. Furthermore, an effective interactive manipulation implies that all the culling computations should be performed for each frame, facing the possibility of fast changes in occlusion information. In this paper, different interactive culling strategies for NURBS surfaces are presented and analyzed. These culling techniques are based on the exploitation of the geometric properties presented in a NURBS surface, that allow easily to find bounds for it in screen space for each frame. Furthermore, the culling overhead for our proposals is small compared to the computational saving, outperforming a proposal without culling. An implementation of these strategies using current GPUs is presented, achieving real-time and interactive rendering rates of complex parametric models.

Parallel hierarchical radiosity on hybrid platforms

Achieving an efficient realistic illumination is an important aim of research in computer graphics. In this paper a new parallel global illumination method for hybrid systems based on the hierarchical radiosity method is presented. Our solution allows the exploitation of systems that combine independent nodes with multiple cores per node. Thus, multiple nodes work in parallel in the computation of the global illumination for the same scene. Within each node, all the available computational cores are used through a shared-memory multithreading approach. The good results obtained in terms of speedup on several distributed-memory and shared-memory configurations show the versatility of our hybrid proposal.

Uniform partitioning of Monte Carlo radiosity on GPUs

The radiosity method permits the obtaining of high quality images through the evaluation of the global illumination of the scene. The computational complexity and the memory requirements of the algorithm are the main problems when a large scene has to be processed. To reduce the memory requirements, Monte Carlo radiosity method is often used. In this paper we present an efficient implementation of the Monte Carlo radiosity algorithm on the GPU using CUDA. We have developed different strategies to increase the performance of the implementation: utilization of an additional simplified version of the mesh to reduce the computational requirements, partitioning of the scene to increase the data locality and an efficient thread scheduling to exploit the characteristics of the GPU. The results are good in terms of execution time, increasing the flexibility of previous solutions.

Hierarchical Radiosity for Multiresolution Systems Based on Normal Tests

The hierarchical radiosity algorithm provides high-quality illumination and the view-independent results obtained can be re-employed for different camera positions. On the other hand, the utilization of multiresolution models is a common solution for the real-time rendering of complex scenes. In this case, the level of detail of each object depends on the specific camera position. Unfortunately, global illumination computations may present an important performance loss in this context. In this paper we present a new solution for hierarchical radiosity for multiresolution systems. Our proposal is based on the application of an enriched hierarchical radiosity algorithm to an input scene with low-resolution objects (represented by coarse meshes) and the efficient data management of the resulting values. The representation of the information we use permits the application of the radiosity values obtained for the coarse version of an object to finer resolution versions of that object. Results of our implementation show that our algorithm produces high-quality images with an important reduction in computational costs.

A high-performance progressive radiosity method based on scene partitioning

The radiosity method is one oft he most popular global illumination models in which highly realistic synthetic images can be achieved. In this paper we present a parallel algorithm for computing the progressive radiosity method on distributed memory systems. Our implementation allows to work with large scenes using a partition of the input scene among the processors; besides good results in terms of speedup have been obtained.