high performance computing on graphics processing units: hgpu.org

Periodic centroidal Voronoi tessellation (CVT) in hyperbolic space provides a nice theoretical framework for computing the constrained CVT on high-genus (genus > 1) surfaces. This paper addresses two computational issues related to such hyperbolic CVT framework: (1) efficient reduction of unnecessary site copies in neighbor domains on the universal covering space, based on two special […]

The benefit of using the Discrete Element Method (DEM) for simulations of fracture in heterogeneous media has been widely highlighted. However modeling large structure leads to prohibitive computations times. We propose to take advantage of Graphics Processor Units (GPUs) to reduce the computation time, taking advantage of the highly data parallel nature of DEM computations. […]

MOTIVATION: The comparison of diverse genomic datasets is fundamental to understanding genome biology. Researchers must explore many large datasets of genome intervals (e.g., genes, sequence alignments) to place their experimental results in a broader context and to make new discoveries. Relationships between genomic datasets are typically measured by identifying intervals that intersect: that is, they […]

We propose a novel convex prior for multilabel optimization which allows to impose arbitrary distances between labels. Only symmetry, d(i; j) >= 0 and d(i; i) = 0 are required. In contrast to previous grid based approaches for the nonmetric case, the proposed prior is formulated in the continuous setting avoiding grid artifacts. In particular, […]

Simulating seismic wave propagation is important for the study of earthquake sources, the generation of strong ground motions and the excitation of large tsunamis. We describe methods for accelerating large-scale finite-difference time-domain simulation of the seismic wave propagation by the use of graphics processing units (GPUs). We then present examples of the wave-filed from the […]

When converting a serial program to a parallel program that can run on a Graphics Processing Unit (GPU) the developer must choose what functions will run on the GPU. For each function the developer chooses, he or she needs to manually write code to: 1) serialize state to GPU memory, 2) define the kernel code […]

Recently alternative approaches in cosmology seeks to explain the nature of dark matter as a direct result of the non-linear spacetime curvature due to different types of deformation potentials. In this context, a key test for this hypothesis is to examine the effects of deformation on the evolution of large scales structures. An important requirement […]

QUAD is a provably secure stream cipher, whose security is based on the hardness assumption of solving multivariate quadratic polynomial systems over a finite field, which is known to be NP-complete. However, such provable security comes at a price, and QUAD is slower than most other stream ciphers that do not have security proofs. In […]

In Content-based Image Retrieval (CBIR) systems, accurately ranking images is of great relevance, since users are interested in the returned images placed at the first positions, which usually are the most relevant ones. In general, CBIR systems consider only pairwise image analysis, that is, compute similarity measures considering only pairs of images, ignoring the rich […]

A computational framework is presented for materials science models that come from energy gradient flows. The models of interest lead to the evolution of structure involving two or more phases. The framework includes higher order derivative models and vector problems. Solutions are considered in periodic cells and standard Fourier spectral discretization in space is used. […]

The growing scale of concurrency requires automated abstraction techniques to cut down the effort in concurrent system analysis. In this paper, we show that the high degree of behavioral symmetry present in GPU programs allows CUDA race detection to be dramatically simplified through abstraction. Our abstraction techniques is one of automatically creating parametric flows

The optimization problem of estimating parameters using a maximum a-posterior (MAP) [3] approach on a non-linear statistical model with a large data set can be solved using an L-BFGS [10] algorithm. When dealing with an ever changing reality, the evaluation need to be fast to capture the immediacy of the observations. This thesis will present […]