high performance computing on graphics processing units: hgpu.org

We take a new approach to interactive visualization and feature detection of large scalar, vector, and multifield computational fluid dynamics data sets that is also well suited for meshless CFD methods. Radial basis functions (RBFs) are used to procedurally encode both scattered and irregular gridded scalar data sets. The RBF encoding creates a complete, unified, […]

Combinational equivalence checking (CEC) is a mainstream application in Electronic Design Automation used to determine the equivalence between two combinational netlists. Tools performing CEC are widely deployed in the design flow to determine the correctness of synthesis transformations and optimizations. One of the main limitations of these tools is their scalability, as industrial scale designs […]

FastSPECT III is a stationary, single-photon emission computed tomography (SPECT) imager designed specifically for imaging and studying neurological pathologies in rodent brain, including Alzheimer’s and Parkinsons’s disease. Twenty independent BazookaSPECT [1] gamma-ray detectors acquire projections of a spherical field of view with pinholes selected for desired resolution and sensitivity. Each BazookaSPECT detector comprises a columnar […]

This article gives an overview on the techniques needed to implement the discrete Fourier transform (DFT) efficiently on current multicore systems. The focus is on Intel-compatible multicores, but we also discuss the IBM Cell and, briefly, graphics processing units (GPUs). The performance optimization is broken down into three key challenges: parallelization, vectorization, and memory hierarchy […]

Tracking-by-detection is increasingly popular in order to tackle the visual tracking problem. Existing adaptive methods suffer from the drifting problem, since they rely on self-updates of an on-line learning method. In contrast to previous work that tackled this problem by employing semi-supervised or multiple-instance learning, we show that augmenting an on-line learning method with complementary […]

This paper reports on the integration of parallel image processing in the ITK library and on improvements to the state-of-the-art of user transparency. In our approach, image processing tasks are wrapped into objects which are passed to the parallel engine. The engine is able to exploit data and task parallelism when executing the tasks on […]

We present a markerless tracking system for unconstrained human motions which are typical for everyday manipulation tasks. Our system is capable of tracking a high-dimensional human model (51 DOF) without constricting the type of motion and the need for training sequences. The system reliably tracks humans that frequently interact with the environment, that manipulate objects, […]

We present an architecture for rendering multiple views efficiently on a cluster of GPUs. The original scene is sampled by virtual cameras which are used later to reconstruct the desired views. We show that this image-based approach can be very scalable and support rendering at interactive rates.

Although stencil auto-tuning has shown tremendous potential in effectively utilizing architectural resources, it has hitherto been limited to single kernel instantiations; in addition, the large variety of stencil kernels used in practice makes this computation pattern difficult to assemble into a library. This work presents a stencil auto-tuning framework that significantly advances programmer productivity by […]

Like many modern techniques for scientific analysis, flow cytometry produces massive amounts of data that must be analyzed and clustered intelligently to be useful. Current manual binning techniques are cumbersome and limited in both the quality and quantity of analysis produced. To address the quality of results, a new framework applying two different sets of […]

In the transversal plane CT exhibits a nearly rotational symmetric point spread function. Pixel sampling is typically done on Cartesian grids which are not ideal from a signal processing point of view. It is advantageous to use a hexagonal grid which can capture the same signal components with 13% fewer sampling points. In 3D one […]

In this article we describe stress nets, a technique for exploring 2D tensor fields. Our method allows a user to examine simultaneously the tensors’ eigenvectors (both major and minor) as well as scalar-valued tensor invariants. By avoiding noise-advection techniques, we are able to display both principal directions of the tensor field as well as the […]