high performance computing on graphics processing units: hgpu.org

The size and resolution of volume datasets in science and medicine are increasing at a rate much greater than the resolution of the screens used to view them. This limits the amount of data that can be viewed simultaneously, potentially leading to a loss of overall context of the data when the user views or […]

We present a system for three-dimensional visualization of complex liquid chromatography-mass spectrometry (LCMS) data. Every LCMS data point has three attributes: time, mass, and intensity. Instead of the traditional visualization of two-dimensional subsets of the data, we visualize it as a height field or terrain in 3D. Unlike traditional terrains, LCMS data has non-linear sampling […]

Modern technology allows the designers of today’s processors to incorporate enormous computation resources into their latest chips. The challenge for these architects is to translate the increase in capability to an increase in performance. The last decade of graphics processor development shows that GPU designers have succeeded spectacularly at this task. In this chapter, we […]

This contribution shows how unsupervised Markovian segmentation techniques can be accelerated when implemented on graphics hardware equipped with a Graphics Processing Unit (GPU). Our strategy exploits the intrinsic properties of local interactions between sites of a Markov Random Field model with the parallel computation ability of a GPU. This paper explains how classical iterative site-wise-update […]

We present a particle system for interactive visualization of steady 3D flow fields on uniform grids. For the amount of particles we target, particle integration needs to be accelerated and the transfer of these sets for rendering must be avoided. To fulfill these requirements, we exploit features of recent graphics accelerators to advect particles in […]

We present algorithms for fast quantile and frequency estimation in large data streams using graphics processors (GPUs). We exploit the high computation power and memory bandwidth of graphics processors and present a new sorting algorithm that performs rasterization operations on the GPUs. We use sorting as the main computational component for histogram approximation and construction […]

GPUs have evolved into powerful and flexible streaming processors with fully programmable floating-point pipelines and tremendous aggregate computational power and memory bandwidth. With these advances, modern GPUs can now perform more functions than the specific graphics computations for which they were designed. This article describes approaches to using GPU processing power to accelerate traditionally CPU-based […]

We present a real-time model-based line tracking approach with adaptive learning of image edge features that can handle partial occlusion and illumination changes. A CAD (VRML) model of the object to track is needed. First, the visible edges of the model with respect to the camera pose estimate are sorted out by a visibility test […]

We present a geometry compression scheme for restricted quadtree meshes and use this scheme for the compression of adaptively triangulated digital elevation models (DEMs). A compression factor of 8-9 is achieved by employing a generalized strip representation of quadtree meshes to incrementally encode vertex positions. In combination with adaptive error-controlled triangulation, this allows us to […]

The proliferation of biological sequence data has motivated the need for an extremely fast probabilistic sequence search. One method for performing this search involves evaluating the Viterbi probability of a hidden Markov model (HMM) of a desired sequence family for each sequence in a protein database. However, one of the difficulties with current implementations is […]

In order to utilize the tremendous computing power of graphics hardware and to automatically adapt to the fast and frequent changes in its architecture and performance characteristics, this paper implements an automatic tuning system to generate high-performance matrix-multiplication implementation on graphics hardware. The automatic tuning system uses a parameterized code generator to generate multiple versions […]

We present algorithms using graphics processing units (GPUs) to efficiently perform database management queries. Our algorithms use efficient data memory representations and storage models on GPUs to perform fast database computations. We present relational database algorithms that successfully exploit the high memory bandwidth and the inherent parallelism available in GPUs. We implement these algorithms on […]