high performance computing on graphics processing units: hgpu.org

LEAP 2013 is the place to learn about and share the latest advances in the use of high-performance parallel computing technology on low-power mobile CPU, GPU, FPGA and embedded processors. Two days of world-class education and networking will give developers, researchers, engineers and technology managers the vital knowledge they need to understand, assess and exploit […]

In the area of computer vision and robotics non-linear optimization methods have become an important tool. For instance, all structure from motion approaches apply optimizations such as bundle adjustment (BA). Most often, the structure of the problem is sparse regarding the functional relations of parameters and measurements. The sparsity of the system has to be […]

The main problem of the kernel density estimation methods is the huge computational requirements, especially for large data sets. One way for accelerating these methods is to use the parallel processing. Recent advances in parallel processing have focused on the use Graphics Processing Units (GPUs) using Compute Unified Device Architecture (CUDA) programming model. In this […]

Tracking sunspots is not an easy task given that multiple sources of data are acquired using a variety of different instruments. With the sources of data and contributors to this repositories quickly growing, it is increasingly important to have an efficient solution to analyze the photographs to record trends and possibly make predictions. CUDA (Compute […]

Gaussian mixture models (GMMs) are often used in various data processing and classification tasks to model a continuous probability density in a multi-dimensional space. In cases, where the dimension of the feature space is relatively high (e.g. in the automatic speech recognition (ASR)), GMM with a higher number of Gaussians with diagonal covariances (DC) instead […]

This thesis focuses on the implementations of a support vector machine (SVM) algorithm on digital signal processor (DSP), graphics processor unit (GPU), and a common Intel i7 core architecture. The purpose of this work is to identify which of the three is most suitable for SVM implementation. The performance is measured by looking at the […]

We present an approach to molecular-dynamics simulations of ferrofluids on graphics processing units (GPUs). Our numerical scheme is based on a GPU-oriented modification of the Barnes-Hut (BH) algorithm designed to increase the parallelism of computations. For an ensemble consisting of a million ferromagnetic particles, the performance of the proposed algorithm on a Tesla M2050 GPU […]

Coarse grain (CG) molecular models have been proposed to simulate complex systems with lower computational overheads and longer timescales with respect to atomistic level models. However, their acceleration on parallel architectures such as graphic processing units (GPUs) presents original challenges that must be carefully evaluated. The objective of this work is to characterize the impact […]

In recent years, with the advance of computing equipment and image acquisition techniques, the sizes, dimensions and content of acquired images have increased considerably. Unfortunately as time passes there is a steadily increasing gap between the classical and parallel programming paradigms and their actual performance on modern computer hardware. In this thesis we consider in […]

The analysis of several algorithms and data structures can be framed as a peeling process on a random hypergraph: vertices with degree less than k are removed until there are no vertices of degree less than k left. The remaining hypergraph is known as the k-core. In this paper, we analyze parallel peeling processes, where […]

Many problems in geophysical and atmospheric modelling require the fast solution of elliptic partial differential equations (PDEs) in "flat" three dimensional geometries. In particular, an anisotropic elliptic PDE for the pressure correction has to be solved at every time step in the dynamical core of many numerical weather prediction models, and equations of a very […]

Stream languages explicitly describe fork-join and pipeline parallelism, offering a powerful programming model for general multicore systems. This parallelism description can be exploited on hybrid architectures, eg. composed of Graphics Processing Units (GPUs) and general purpose multicore processors. In this paper, we present a novel approach to optimize stream programs for hybrid architectures composed of […]