high performance computing on graphics processing units: hgpu.org

Web technologies provide the basis to distribute digital information worldwide and in realtime but they have also established the Web as a ubiquitous application platform. The Web evolved from simple text data to include advanced layout, images, audio, and recently streaming video. Today, as our digital environment becomes increasingly three-dimensional (e.g. 3D cinema, 3D video, […]

In creating complex real-time shaders, programmers should be able to decompose code into independent, localized modules of their choosing. Current real-time shading languages, however, enforce a fixed decomposition into per-pipeline-stage procedures. Program concerns at other scales — including those that cross-cut multiple pipeline stages — cannot be expressed as reusable modules. We present a shading […]

We present a highly exible and efficient software pipeline for programmable triangle voxelization. The pipeline, entirely written in CUDA, supports both fully conservative and thin voxelizations, multiple boolean, floating point, vector-typed render targets, user-defined vertex and fragment shaders, and a bucketing mode which can be used to generate 3D A-buffers containing the entire list of […]

Manycore accelerators such as graphics processor units (GPUs) organize processing units into single-instruction, multiple data "cores" to improve throughput per unit hardware cost. Programming models for these accelerators encourage applications to run kernels with large groups of parallel scalar threads. The hardware groups these threads into warps/wavefronts and executes them in lockstep-dubbed single-instruction, multiple-thread (SIMT) […]

Probabilistic Latent Semantic Analysis (PLSA) has been successfully applied to many text mining tasks such as retrieval, clustering, summarization, etc. PLSA involves iterative computation for a large number of parameters and may take hours or even days to process a large dataset, thus speeding up PLSA is highly motivated in the domain of text mining. […]

The paper deals with potentialities of various up-to-date software development tools for making use of graphic processor (GPU) parallel computing resources. Examples are given to illustrate the use of present-day software tools for the development of applications and realization of algorithms for scientific-technical calculations performed by GPGPU. The paper presents some classes of hard mathematical […]

On-line Machine Learning using Stochastic Gradient Descent is an inherently sequential computation. This makes it difficult to improve performance by simply employing parallel architectures. Langford et al. made a modification to the standard stochastic gradient descent approach which opens up the possibility of parallel computation. They also proved that there is no significant loss in […]

In volume visualization, the definition of the regions of interest is inherently an iterative trial-and-error process finding out the best parameters to classify and render the final image. Generally, the user requires a lot of expertise to analyze and edit these parameters through multi-dimensional transfer functions. In this paper, we present a framework of intelligent […]

Frequent itemset mining from uncertain databases is different from conventional one in the sense that it needs to take into account uncertainty. To this end, some methods have already been proposed, but their performances are not satisfactory. Meanwhile, GPGPU (General Purpose computing on GPU) have recently been an interesting research subject in the field of […]

We investigate new programming techniques for parallel tempering Monte Carlo simulations of an elementary bead-spring homopolymer model using graphics processing units (GPUs). For a precise estimation of statistical quantities, like the peak structure of the specific heat, a large number of conformations with substantial statistical data is needed. Therefore the advantage of gathering this data […]

In this work we analyze an open-source multifrontal solver implementation (UMFPACK) and modify it to transfer the computation load on an OpenCL device, typically a GPU. To achieve this result the dbOpenCL library has been created, which allows a neat integration of OpenCL code into existent C or C++ code. An analysis and pro ling […]

The main objective of this work is to explore the capacity of modern GPUs to accelerate the ICON (ICOsahedral Non-hydrostatic) model [4] developed by the Max-Planck-Institut fur Meteorologie (MPI-M) in Hamburg in collaboration with the Deutscher Wetterdienst (DWD). The ICON model is an atmospheric general circulation model suited for both global and regional scale simulation.