Multi-GPU support on the marrow algorithmic skeleton framework

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

Valorization of grape pomace residues integrating hot compressed water with biotechnology

Dissertação para obtenção do grau de Mestre em Biotecnologia

SPf66 vaccine trial in Brazil: conceptual framework study design and analytical approach

This paper describes the study population and the study design of the phase III field trial of the SPf66 vaccine in Brazil. Assessment of validity and precision principles necessary for the appropriate evaluation of the protective effect of the vaccine are discussed, as well as the results of the preliminary analyses of the gathered data. The analytical approach for the estimation of the protective effect of the vaccine is presented. This paper provides the conceptual framework for future publications.

Framework para a construção de “portais de negócio” para gestão de solicitações de consumidores IaaS na HP Cloud

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

Gas adsorption in the MIL-53(AI) metal organic framework. Experiments and molecular simulation

Dissertação para obtenção do Grau de Doutor em Engenharia Química

Fluvial system restoration – case study: river Tua

Dissertação para obtenção do Grau de Mestre em Engenharia do Ambiente, Perfil de Engenharia de Sistemas Ambientais

A framework for developing motion-based games

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

Coherent structures in open channel flows with bed load transport over an hydraulically rough bed

Dissertação para obtenção do Grau de Mestre em Engenharia Civil – Perfil de Estruturas

Cost efficiency in the Portuguese water sector: The case of multimunicipal systems operating at the bulk level

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Economics from the NOVA – School of Business and Economics

The building blocks of social entrepreneurship: empirical model and framework

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

Diallelic analysis to obtain cowpea (Vigna unguiculata L. Walp.) populations tolerant to water deficit.

The purpose of this study was to identify parents and obtain segregating populations of cowpea (Vigna unguiculata L. Walp.) with the potential for tolerance to water deficit. A full diallel was performed with six cowpea genotypes, and two experiments were conducted in Teresina, PI, Brazil in 2011 to evaluate 30 F2 populations and their parents, one under water deficit and the other under full irrigation.

Integration of Membrane Filtration and Photolysis Processes for Drinking Water Treatment

Dissertation presented to obtain the Ph.D degree in Engineering and Technology Sciences, Chemical Engineering.

A knowledge-based framework to facilitate E-training implementation

Dissertação para obtenção do Grau de Mestre em Engenharia Eletrotécnica e de Computadores

Potential for ORC application in the Portuguese manufacturing industry

Dissertação para obtenção do Grau de Mestre em Engenharia do Ambiente, perfil Gestão e Sistemas Ambientais

Heterogeneous computing with an algorithmic skeleton framework

The Graphics Processing Unit (GPU) is present in almost every modern day personal computer. Despite its specific purpose design, they have been increasingly used for general computations with very good results. Hence, there is a growing effort from the community to seamlessly integrate this kind of devices in everyday computing. However, to fully exploit the potential of a system comprising GPUs and CPUs, these devices should be presented to the programmer as a single platform. The efficient combination of the power of CPU and GPU devices is highly dependent on each device’s characteristics, resulting in platform specific applications that cannot be ported to different systems. Also, the most efficient work balance among devices is highly dependable on the computations to be performed and respective data sizes. In this work, we propose a solution for heterogeneous environments based on the abstraction level provided by algorithmic skeletons. Our goal is to take full advantage of the power of all CPU and GPU devices present in a system, without the need for different kernel implementations nor explicit work-distribution.To that end, we extended Marrow, an algorithmic skeleton framework for multi-GPUs, to support CPU computations and efficiently balance the work-load between devices. Our approach is based on an offline training execution that identifies the ideal work balance and platform configurations for a given application and input data size. The evaluation of this work shows that the combination of CPU and GPU devices can significantly boost the performance of our benchmarks in the tested environments, when compared to GPU-only executions.