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Original title (Portuguese): Simulação e análise de algoritmos para a era multicore
Period: 2010-11 to 2012-10
Funding agency: Conselho Nacional de Desenvolvimento Científico e Tecnológico
Original title (Portuguese): Codificação de Canal Energeticamente Eficiente Aplicada a Redes de Sensores sem Fio
Period: 2018-08 to 2020-08
Funding agency: Universidade Federal do Rio Grande do Norte
Original title (Portuguese): Ampliação e consolidação da infraestrutura de pesquisa e pós-graduação da UFRN
Period: 2013-12 to 2020-12
Funding agency: Financiadora de Estudos e Projetos
Description: The goal of this project was to establish a scientific computing centre starting from acquiring and making operational a high-performance computing infrastructure.
Original title (Portuguese): Concepção e Desenvolvimento de um Receptor de Baixa Complexidade para Sistemas com Transmissão em Diversidade Wavelet-Tempo sobre Canais com Desvanecimento Plano
Period: 2017-08 to 2019-08
Funding agency: Universidade Federal do Rio Grande do Norte
Period: 2016-12-01 to 2018-12-01
Funding agency: The Royal Society
Original title (Portuguese): Sistema de Rádio Definido por Software com Modulação Codificada por Wavelets
Period: 2012-08 to 2014-08
Funding agency: Universidade Federal do Rio Grande do Norte
Original title (Portuguese): Processador de Múltiplos Núcleos de Baixa Frequência para Processamento-a-Bordo Energeticamente Eficiente em Sistemas Aeroespaciais
Period: 2017-11 to 2020-10
Funding agency: Conselho Nacional de Desenvolvimento Científico e Tecnológico
Period: 2018-01 to 2018-12
Funding agency: State Secretariat for Education, Research and Innovation SERI
Description: The goal of this collaboration project is putting together a methodology for power modeling and application characterization under varying parallelism with a energy-efficient machine-learning based hierarchical approach towards server virtualization and resource allocation. The combination of both domains will ultimately lead towards the development of a more general energy-aware framework for next-generation Quality-of-Service constrained and big-data virtualized applications. This framework will enable the efficient deployment of applications with varying degrees of parallelism and spanning among a virtualized multi-core server or a set of servers, following the paradigm of software-defined servers, and handling big-data problems that are unfeasible today.
Original title (Portuguese): Software paralelo energeticamente eficiente para processadores heterogêneos
Period: 2020-05 to 2022-04
Funding agency: Universidade Federal do Rio Grande do Norte