high performance computing on graphics processing units: hgpu.org

The paper focuses on the FraDIA vision subsystem part responsible for GPU-based image processing. The developed set of classes encapsulates the OpenCL subroutines and utilizes GPU to fulfill the robotic requirements for real-time visual data processing. The class structure reflects the proposed classification of image processing algorithms.

Since real-time acquisition of 3D echocardiographic data is achievable in practice, many volume rendering algorithms have been proposed for visualization purposes. However, due to the large amounts of data and computations involved a tradeoff between image quality and computational efficiency has to be made. The main goal of our study was to generate high quality […]

In the last decade, there has been a dramatic growth in research and development of massively parallel many-core architectures like graphics hardware, both in academia and industry. This changed also the way programs are written in order to leverage the processing power of a multitude of cores on the same hardware. In the beginning, programmers […]

The electrical and electronic engineering has used parallel programming to solve its large scale complex problems for performance reasons. However, as parallel programming requires a non-trivial distribution of tasks and data, developers find it hard to implement their applications effectively. Thus, in order to reduce design complexity, we propose an approach to generate code for […]

MOTIVATION: Data clustering techniques are an essential component of a good data analysis toolbox. Many current bioinformatics applications are inherently compute-intense and work with very large data sets. Sequential algorithms are inadequate for providing the necessary performance. For this reason, we have created CAMPAIGN, a central resource for data clustering algorithms and tools that are […]

We report on our implementation of the RHMC algorithm for the simulation of lattice QCD with two staggered flavors on Graphics Processing Units, using the NVIDIA CUDA programming language. The main feature of our code is that the GPU is not used just as an accelerator, but instead the whole Molecular Dynamics trajectory is performed […]

Compton reconstruction requires the computationally intensive, yet highly parallelizable, task of Cone of Response (CoR) back-projection. The acceleration of CoR back-projection is of significant importance as a faster algorithm allows the user to increase either the size or resolution of the imaging volume. Such acceleration also lends itself to the realization of real-time reconstruction. The […]

The programmability of recent graphic processing unit (GPU) architectures has been the main factor driving the dramatic increase in interest for this class of architectures as low-cost accelerators for a wide range of high-performance applications. Current GPU programming models, such as OpenCL and CUDA, still expose too many architectural features, such as the memory hierarchy, […]

The recent interest in GPGPU, (General-Purpose computation on Graphics Processing Unit), has stimulated improvements in the programmability of the GPU. Although the utilization of new languages like OpenCL and CUDA facilitate GPU programming, different challenges have to be overcome to optimize the results of a direct implementation. Specifically, a straightforward implementation of the Monte Carlo […]

Recently, General Purpose Graphical Processing Units (GP-GPUs) have been identified as an intriguing technology to accelerate numerous data-parallel algorithms. Several GPU architectures and programming models are beginning to emerge and establish their niche in the High-Performance Computing (HPC) community. New massively parallel architectures such as the Nvidia’s Fermi and AMD/ATi’s Radeon pack tremendous computing power […]

We present parallel algorithms for constructing and traversing sparse octrees on graphics processing units (GPUs). The algorithms are based on parallel-scan and sort methods. To test the performance and feasibility, we implemented them in CUDA in the form of a gravitational tree-code which completely runs on the GPU.(The code is publicly available at: http://castle.strw.leidenuniv.nl/software.html) The […]

Held in conjunction with PACT 2011. GPUs are cost-effective platforms for computational intensive applications providing tremendous peak performance. However, it is a major challenge to deliver the intrinsic performance of such architectures to end applications. The goal of this workshop is to bring together GPU experts with computational science experts. The workshop addresses programming approaches […]