Desenvolvimento de aplicações que marcam presença na web

O principal objectivo deste relatório é documentar a experiência como estagiário na empresa The Silver Factory – Marketing, Design e Gestão Comercial, Lda, no âmbito da unidade curricular de Estágio do Mestrado em Engenharia-Informática – Computação Móvel (MEI-CM). Sendo este estágio uma parte integrante para a obtenção do grau de Mestre, foram postos em prática conhecimentos adquiridos ao longo do meu percurso universitário (Licenciatura e 1º ano de Mestrado) de modo a concluir com sucesso todos os projetos que me foram propostos. Durante este estágio trabalhei na área da comunicação online, através do desenvolvimento de websites e auxiliando na gestão do alojamento dos clientes. O principal objetivo foi desenvolver um backoffice e os seus respetivos componentes. Dos vários componentes desenvolvidos os mais importantes foram o Content Management System que permite fazer a gestão do conteúdo apresentado em frontend, e o Projetct Management Tool, que permite a uma empresa gerir os seus clientes, e os projetos que desenvolve para os mesmos, com a possibilidade de visualização do progresso de desenvolvimento desses projetos utilizando um gráfico de Gantt interativo.

Optimization of Pattern Matching Algorithms for Multi- and Many-Core Platforms

Image and video compression play a major role in the world today, allowing the storage and transmission of large multimedia content volumes. However, the processing of this information requires high computational resources, hence the improvement of the computational performance of these compression algorithms is very important. The Multidimensional Multiscale Parser (MMP) is a pattern-matching-based compression algorithm for multimedia contents, namely images, achieving high compression ratios, maintaining good image quality, Rodrigues et al. [2008]. However, in comparison with other existing algorithms, this algorithm takes some time to execute. Therefore, two parallel implementations for GPUs were proposed by Ribeiro [2016] and Silva [2015] in CUDA and OpenCL-GPU, respectively. In this dissertation, to complement the referred work, we propose two parallel versions that run the MMP algorithm in CPU: one resorting to OpenMP and another that converts the existing OpenCL-GPU into OpenCL-CPU. The proposed solutions are able to improve the computational performance of MMP by 3 and 2:7 , respectively. The High Efficiency Video Coding (HEVC/H.265) is the most recent standard for compression of image and video. Its impressive compression performance, makes it a target for many adaptations, particularly for holoscopic image/video processing (or light field). Some of the proposed modifications to encode this new multimedia content are based on geometry-based disparity compensations (SS), developed by Conti et al. [2014], and a Geometric Transformations (GT) module, proposed by Monteiro et al. [2015]. These compression algorithms for holoscopic images based on HEVC present an implementation of specific search for similar micro-images that is more efficient than the one performed by HEVC, but its implementation is considerably slower than HEVC. In order to enable better execution times, we choose to use the OpenCL API as the GPU enabling language in order to increase the module performance. With its most costly setting, we are able to reduce the GT module execution time from 6.9 days to less then 4 hours, effectively attaining a speedup of 45 .