Margarita Amor

Hardware support for adaptive subdivision surface rendering

Adaptive subdivision of triangular meshes is highly desirable for surface generation algorithms including adaptive displacement mapping in which a highly detailed model can be constructed from a coarse triangle mesh and a displacement map. The communication requirements between the CPU and the graphics pipeline can be reduced if more detailed and complex surfaces are generated, as in displacement mapping, by an adaptive tessellation unit which is part of the graphics pipeline. Generating subdivision surfaces requires a large amount of memory in whicmultiple arbitrary accesses are required to neighbouring vertices to calculate the new vertices. In this paper we present a meshing scheme and new architecture for the implementation of adaptive subdivision of triangular meshes that allows for quick access using a small memory making it feasible in hardware, while at the same time allowing for new vertices to be adaptively inserted. The architecutre is regular and characterized by an efficient data management that minimizes the data storage and avoids the wait cycles that would be associated with the multiple data accesses required for traditional subdivision. This architecture is presented as an improvement for adaptive displacement mapping algorithms, but could also be used for adaptive subdivision surface generation in hardware.

A Data-Parallel Formulation for Divide and Conquer Algorithms

This paper presents a general data-parallel formulation for a class of problems based on the divide and conquer strategy. A combination of three techniques—mapping vectors, index-digit permutations and space-filling curves—are used to reorganize the algorithmic dataflow, providing great flexibility to efficiently exploit data locality and to reduce and optimize communications. In addition, these techniques allow the easy translation of the reorganized dataflows into HPF (High Performance Fortran) constructs. Finally, experimental results on the Cray T3E validate our method.

A multi‐GPU shallow‐water simulation with transport of contaminants

This work presents cost‐effective multi‐graphics processing unit (GPU) parallel implementations of a finite‐volume numerical scheme for solving pollutant transport problems in bidimensional domains. The fluid is modeled by 2D shallow‐water equations, whereas the transport of pollutant is modeled by a transport equation. The 2D domain is discretized using a first‐order Roe finite‐volume scheme. Specifically, this paper presents multi‐GPU implementations of both a solution that exploits recomputation on the GPU and an optimized solution that is based on a ghost cell decoupling approach. Our multi‐GPU implementations have been optimized using nonblocking communications, overlapping communications and computations and the application of ghost cell expansion to minimize communications. The fastest one reached a speedup of 78 × using four GPUs on an InfiniBand network with respect to a parallel execution on a multicore CPU with six cores and two‐way hyperthreading per core. Such performance, measured using a realistic problem, enabled the calculation of solutions not only in real time but also in orders of magnitude faster than the simulated time.Copyright

Extended hybrid meshing algorithm for multiresolution terrain models

Hybrid terrains are a convenient approach for the representation of digital terrain models, integrating heterogeneous data from different sources. In this article, we present a general, efficient scheme for achieving interactive level-of-detail rendering of hybrid terrain models, without the need for a costly preprocessing or resampling of the original data. The presented method works with hybrid digital terrains combining regular grid data and local high-resolution triangulated irregular networks. Since grid and triangulated irregular network data may belong to different datasets, a straightforward combination of both geometries would lead to meshes with holes and overlapping triangles. Our method generates a single multiresolution model integrating the different parts in a coherent way, by performing an adaptive tessellation of the region between their boundaries. Hence, our solution is one of the few existing approaches for integrating different multiresolution algorithms within the same terrain model, achieving a simple interactive rendering of complex hybrid terrains.

FFT Implementation on a Streaming Architecture

Fast Fourier Transform (FFT) is a useful tool for applications requiring signal analysis and processing. However, its high computational cost requires efficient implementations, specially if real time applications are used, where response time is a decisive factor. Thus, the computational cost and wide application range that requires FFT transforms has motivated the research of efficient implementations. Recently, GPU computing is becoming more and more relevant because of their high computational power and low cost, but due to its novelty there is some lack of tools and libraries. In this paper we propose an efficient implementation of the FFT with AMDs Brook+ language. We describe several features and optimization strategies, analyzing the scalability and performance compared to other well-known existing solutions.

Unified Hybrid Terrain Representation Based on Local Convexifications

Hybrid digital terrain models represent an effective framework to combine and integrate terrain data with different topology and resolution. Cartographic digital terrain models typically are constituted by regular grid data and can be refined by adding locally TINs that represent morphologically complex terrain parts. Direct rendering of both data sets to visualize the digital terrain model would generate geometric discontinuities as the meshes are disconnected. In this paper we present a new meshing scheme for hybrid terrain representations. High quality models without discontinuities are generated as the different representations are softly joined through an adaptive tessellation procedure. Due to the complexity of the algorithms involved in the tessellation procedure, we propose a mixed strategy where part of the information is pre-computed and efficiently encoded. This way, for rendering the model, the tessellation information has to be decoded and only additional simple operations have to be performed.

FFTs on mesh connected computers

The most effective use of mesh connected computers is achieved by paying careful attention to the organization of the storage and movement of data. For an important class of algorithms the formalization of the different operations they perform lead to an unified treatment for them and may result in important simplifications. In this work we apply this point of view to the Fast Fourier Transform (FFT). In particular, we present a unified view of a set of FFT algorithms on mesh connected computers with non-shared memory. To this end we use a combination of two techniques, `mapping vector? and index-digit permutations, which allow us to define the organization of the storage and movement of data for any FFT algorithm whose radix is a power of 2. The methodology we have employed is general and can be applied to other algorithms obtained through the divide and conquer strategy.

A meshing scheme for efficient hardware implementation of butterfly subdivision using displacement mapping

Displacement mapping is an effective technique for encoding the high levels of detail of surface models using coarse triangle meshes and displacement maps. These maps are 2D representations containing the distances between the coarse mesh and the surface to represent. Displacement maps have been used in many applications such as ray tracing, image warping, and volume rendering. In this article, we propose modifications to our previous grouping strategy, a new subdivision strategy based on the Modified Butterfly algorithm and new heuristics for the adaptive subdivision procedure, and, finally, the corresponding modifications on our hardware proposal. A meshing scheme and an adaptive subdivision strategy based on displacement mapping reduce the bottleneck between the CPU and graphics pipeline common in high-performance graphics systems.

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.

A Data Parallel Formulation of the Barnes-Hut Method for N -Body Simulations

This paper presents a data-parallel formulation for N-body simulations using the Barnes-Hut method. The tree-structured problem is first linearized by using space-filling curves. This process allows us to use standard data distributions and parallel array operations available in data-parallel languages. A new efficient HPF implementation of the Barnes-Hut method is presented in this paper, characterized by the use of array copy sections to express communications, obtaining efficient point-to-point data transferences. In addition, HPF LOCAL constructs are used to obtain very compact and efficient local (node) codes.