Evolução cosmológica de perturbações de densidade inhomogêneas

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Tunable Fermi acceleration in a nondissipative driven magnetic billiard

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Zero, minimum and maximum relative radial acceleration for planar formation flight dynamics near triangular libration points in the Earth-Moon system

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Vacuum polarization by a magnetic flux in a cosmic string background.

In this paper we analyse the vacuum polarization effects due to a magnetic flux on massless fermionic fields in a cosmic string background. Three distinct configurations of magnetic fields are considered. In all of them the magnetic fluxes are confined in a long cylindrical tube of finite radius.

Some remarks on the attractor behaviour in ELKO cosmology

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Alignment of the CMS tracker with LHC and cosmic ray data

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Image Re-Ranking Acceleration on GPUs

Huge image collections are becoming available lately. In this scenario, the use of Content-Based Image Retrieval (CBIR) systems has emerged as a promising approach to support image searches. The objective of CBIR systems is to retrieve the most similar images in a collection, given a query image, by taking into account image visual properties such as texture, color, and shape. In these systems, the effectiveness of the retrieval process depends heavily on the accuracy of ranking approaches. Recently, re-ranking approaches have been proposed to improve the effectiveness of CBIR systems by taking into account the relationships among images. The re-ranking approaches consider the relationships among all images in a given dataset. These approaches typically demands a huge amount of computational power, which hampers its use in practical situations. On the other hand, these methods can be massively parallelized. In this paper, we propose to speedup the computation of the RL-Sim algorithm, a recently proposed image re-ranking approach, by using the computational power of Graphics Processing Units (GPU). GPUs are emerging as relatively inexpensive parallel processors that are becoming available on a wide range of computer systems. We address the image re-ranking performance challenges by proposing a parallel solution designed to fit the computational model of GPUs. We conducted an experimental evaluation considering different implementations and devices. Experimental results demonstrate that significant performance gains can be obtained. Our approach achieves speedups of 7x from serial implementation considering the overall algorithm and up to 36x on its core steps.

Global ballistic acceleration in a bouncing-ball model

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Equação de Estado para o Universo Primordial

Pós-graduação em Física - IFT