high performance computing on graphics processing units: hgpu.org

We present a CUDA implementation of dense multivariate polynomial arithmetic based on Fast Fourier Transforms over finite fields. Our core routine computes on the device (GPU) the subresultant chain of two polynomials with respect to a given variable. This subresultant chain is encoded by values on a FFT grid and is manipulated from the host […]

Analyzing and clustering large scale data set is a complex problem. One explored method of solving this problem borrows from nature, imitating the flocking behavior of birds. One limitation of this method of data clustering is its complexity O(n^2). As the number of data and feature dimensions grows, it becomes increasingly difficult to generate results […]

In this paper we describe GPA priori, a GPU-accelerated implementation of Frequent Item set Mining (FIM). We tested our implementation with an Nvidia Tesla T10 graphic processor and demonstrate up to 100x speedup as compared with several state-of-the-art FIM algorithms on a CPU. In order to map the Apriori algorithm onto the SIMD execution model, […]

Recent technological developments made various many-core hardware platforms widely accessible. These massively parallel architectures have been used to significantly accelerate many computation demanding tasks. In this paper, we show how the algorithms for LTL model checking can be redesigned in order to accelerate LTL model checking on many-core GPU platforms. Our detailed experimental evaluation demonstrates […]

Optical techniques are a promising technology to realize high frequency ultrasound arrays. High sensitivity and broad bandwidth have been demonstrated with optoacoustic sensors based on thin film etalons. A thin film etalon consists of a transparent layer (e.g. photoresist or parylene) with gold coatings on a glass substrate. One-dimensional (1-D) data acquisition is realized by […]

This paper presents a hybrid photon-mapping approach for global illumination. It represents a significant improvement over a previously described approach, both with respect to speed and accuracy. Using OptiX for ray tracing provides a considerable improvement in the speed of ray tracing and would keep synchronization to a minimum by using texture memory to cache […]

We develop GPU adaptations of the Aho-Corasick string matching algorithm for the the case when all data reside initially in the GPU memory and the results are to be left in this memory. We consider several refinements to a base GPU implementation and measure the performance gain from each refinement. Experiments conducted on an NVIDIA […]

Network science makes heavy use of simulation models and calculations based upon graph-oriented data structures that are intrinsically highly irregular in nature. The key to efficient use of data-parallel and multi-core parallelism on graphical processing units (GPUs) and CPUs is often to optimise the data layout and to exploit distributed memory locality with processing elements. […]

The numerical solutions of Shallow Water Equations are useful for applications related to geophysical flows that usually take place in large computational domains and could require real time calculation. Therefore, parallel versions of accurate and efficient numerical solvers for high performance platforms are needed to be able to deal with these simulation scenarios in reasonable […]

This paper describes the parallel SIFT-detector implementation on the basis of the NVIDIA CUDA technology for the images matching. The SIFT-detector implementation was applied for the images matching in the stereo-system mounted on the moving car and for images from the onboard UAV-camera.

The PageRank algorithm for determining the "importance" of Web pages forms the core component of Google’s search technology. As the Web graph is very large, containing over a billion nodes, PageRank is generally computed offline, during the preprocessing of the Web crawl, before any queries have been issued. Viewed mathematically, PageRank is nothing but the […]

Image inpainting refers to the process of reconstructing the original image from a damaged one in a visually plausible way. We propose a new gradientbased algorithm for exemplar-based inpainting by making use of L1 norm. We implement the most time consuming step of the algorithm on the GPU and compare the serial execution timings against […]