high performance computing on graphics processing units: hgpu.org

Point target analysis is an important tool to analyze the quality of SAR images. To permit interactive visual analysis, visualization applications need to automatically detect point targets in a SAR image and estimate associated quality measurements such as the peak sidelobe ratio (PSLR). This task is computationally expensive. In this paper, we propose methods for […]

We propose a method to determine the optimal camera alignment for a tracking system with multiple cameras by specifying the volume to be tracked and an initial camera setup. We use optimization strategies based on methods usually employed for solving nonlinear systems of equations. All approaches are fully automatic and take advantage of modern graphics […]

Usage of statistical classifiers, namely AdaBoost and its modifications, in object detection and pattern recognition is a contemporary and popular trend. The computatiponal performance of these classifiers largely depends on low level image features they are using: both from the point of view of the amount of information the feature provides and the executional time […]

Parallel Implementation of Evolutionary Algorithms There is growing interest in running evolutionary computation on Parallel Implementation of Evolutionary Algorithms. A number of technologies are already available. These include Grid and Cloud Computing, Internet Computing (e.g. seti@home, boinc), General Purpose Computation on Graphics Processing Units (GPGPU), multi-core and many-core architectures and supercomputers. Although they are routinely […]

We present an approach to navigation planning for humanoid robots that aims to ensure reliable execution by augmenting the planning process to reason about the robotpsilas ability to successfully perceive its environment during operation. By efficiently simulating the robotpsilas perception system during search, our planner generates a metric, the so-called perceptive capability, that quantifies the […]

A major bottleneck in molecular dynamics (MD) simulations is the calculation of the pair wise nonbonded interactions. Previous work on FPGAs has shown that these calculations can be implemented with a number of force computation pipelines operating in parallel (4 and 8 for the Stratix-III and Stratix-V, respectively). Optimization has received some attention previously in […]

Modelling the interactions of biological molecules, or docking, is critical both to understanding basic life processes and to designing new drugs. The field programmable gate array (FPGA) based acceleration of a recently developed, complex, production docking code is described. The authors found that it is necessary to extend their previous three-dimensional (3D) correlation structure in […]

In this paper, we present the first algorithm to geometrically register multiple projectors in a view-independent manner (i.e. wallpapered) on a common type of curved surface, vertically extruded surface, using an uncalibrated camera without attaching any obtrusive markers to the display screen. Further, it can also tolerate large non-linear geometric distortions in the projectors as […]

We give a brief discussion of denoising algorithms for depth data and introduce a novel technique based on the NL-means filter. A unified approach is presented that removes outliers from depth data and accordingly achieves an unbiased smoothing result. This robust denoising algorithm takes intra-patch similarity and optional color information into account in order to […]

Spatial/spectral algorithms have been shown in previous work to be a promising approach to the problem of extracting image end members from remotely sensed hyperspectral data. Such algorithms map nicely on high-performance systems such as massively parallel clusters and networks of computers. Unfortunately, these systems are generally expensive and difficult to adapt to onboard data […]

Support Vector Machines (SVMs) are a powerful supervised learning tool, providing state-of-the-art accuracy at a cost of high computational complexity. The SVM classification suffers from linear dependencies on the number of the Support Vectors and the problem’s dimensionality. In this work, we propose a scalable FPGA architecture for the acceleration of SVM classification, which exploits […]

Continuing improvements in CPU and GPU performances as well as increasing multi-core processor and cluster-based parallelism demand for flexible and scalable parallel rendering solutions that can exploit multipipe hardware accelerated graphics. In fact, to achieve interactive visualization, scalable rendering systems are essential to cope with the rapid growth of data sets. However, parallel rendering systems […]