high performance computing on graphics processing units: hgpu.org

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.

Parallel and heterogeneous computing are growing in audience thanks to the increased performance brought by ubiquitous manycores and GPUs. However, available programming models, like OPENCL or CUDA, are far from being straightforward to use. As a consequence, several automated or semi-automated approaches have been proposed to automatically generate hardware-level codes from high-level sequential sources. Polyhedral […]

E(A+M)PEC traces the ionization structure, cooling and emission spectra of plasmas. It is written in OpenCL, runs in NVIDIA Graphics Processor Units and can be coupled to any HD or MHD code to follow the dynamical and thermal evolution of any plasma in, e.g., the interstellar medium (ISM).

General-purpose computing on graphics processing units, also known as GPGPU, is a burgeoning technique to enhance the computation of parallel programs. Applying this technique to real-time applications, however, requires additional support for timeliness of execution. In particular, the non-preemptive nature of GPGPU, associated with copying data to/from the device memory and launching code onto the […]

Mining the increasing amount of genomic data requires having very efficient tools. Increasing the efficiency can be obtained with better algorithms, but one could also take advantage of the hardware itself to reduce the application runtimes. Since a few years, issues with heat dissipation prevent the processors from having higher frequencies. One of the answers […]