high performance computing on graphics processing units: hgpu.org

Real-time rendering of large animated crowds consisting thousands of virtual humans is important for several applications including simulations, games and interactive walkthroughs, but cannot be performed using complex polygonal models at interactive frame rates. For that reason, several methods using large numbers of pre-computed image-based representations, which are called as impostors, have been proposed. These […]

An on-line web application that interacts with an Internet user’s 3D webcam (e.g. Minoru stereo webcamera) is described. The application instantly captures and processes stereo images to retrieve 3D object coordinates for further 3D modelling tasks. It offers on-demand semi-automatic camera calibration and automatic image pair rectification for further stereo matching operations. The reconstructed 3D […]

In this paper we present a new pseudorandom number generator (PRNG) on graphics processing units (GPU). This PRNG is based on the so-called chaotic iterations. It is firstly proven to be chaotic according to the Devaney’s formulation. We thus propose an efficient implementation for GPU that successfully passes the BigCrush tests, deemed to be the […]

We report on our implementation of LatticeQCD applications using OpenCL. We focus on the general concept and on distributing different parts on hybrid systems, consisting of both CPUs (Central Processing Units) and GPUs (Graphic Processing Units).

Image recognition systems require large image data sets for the training process. The annotation of such data sets through users requires a lot of time and effort, and thereby presents the bottleneck in the development of recognition systems. In order to simplify the creation of image recognition systems it is necessary to develop interaction concepts […]

Beginning with Amdahl’s law, we derive a general objective function that links parallel processing performance gains at the system level, to energy and delay in the sub-system microarchitecture structures. The objective function employs parameterized models of computation and communication to represent the characteristics of processors, memories, and communications networks. The interaction of the latter microarchitectural […]

In this paper, we analyze the potential of asynchronous relaxation methods on Graphics Processing Units (GPUs). For this purpose, we developed a set of asynchronous iteration algorithms in CUDA and compared them with a parallel implementation of synchronous relaxation methods on CPU-based systems. For a set of test matrices taken from the University of Florida […]

Current video cards (GPUs – Graphics Processing Units) are very programmable, have become much more powerful than the CPUs and they are very affordable. In this paper, we present an implementation for the AES algorithm using Direct3D 10 certified GPUs. The graphics API Direct3D 10 is the first version that allows the use of integer […]

We present parallel algorithms to accelerate collision queries for sample-based motion planning. Our approach is designed for current many-core GPUs and exploits the data-parallelism and multi-threaded capabilities. In order to take advantage of high number of cores, we present a clustering scheme and collision-packet traversal to perform efficient collision queries on multiple configurations simultaneously. Furthermore, […]

In this paper, we present an efficient implementation of a state-of-the-art high-resolution explicit scheme for the shallow water equations on graphics processing units. The selected scheme is well-balanced, supports dry states, and is particularly suitable for implementation on graphics processing units. We verify and validate our implementation, and show that use of efficient single precision […]

This thesis describes a generative programming system that automatically constructs parallel simulations of complex systems that are based on field equations using finite differencing and explicit Runge-Kutta integration methods. Programming computational simulations by hand for different parallel architectures is both tedious and time consuming. Simulation frameworks struggle to target different architectures without losing performance. Automating […]

Despite the ability of current GPU processors to treat heavy parallel computation tasks, its use for solving medical image segmentation problems is still not fully exploited and remains challenging. A lot of difficulties may arise related to, for example, the different image modalities, noise and artifacts of source images, or the shape and appearance variability […]