High-Performance Computing and Cloud Computing
The area of High-Performance Computing (HPC) and Cloud Computing is a dynamic and essential field in computer science, focused on the development and application of advanced computing systems capable of processing large amounts of data at extremely high speeds. High-Performance Computing involves the use of supercomputers and parallel processing systems to solve complex and processing-intensive problems. Meanwhile, Cloud Computing refers to the use of computing resources (such as servers, storage, databases, networks, software) over the internet, offering scalability, flexibility, and cost efficiency.
About the Area Coordinator
Prof. Daniel Sundfeld Lima
At CEDIS, the integration of High-Performance Computing and Cloud Computing is a research and development area of great interest. Coordinated by Prof. Daniel Sundfeld, this research line explores how these two technologies can be combined to offer more powerful and efficient solutions. The research team, comprised of experts in system architecture, computer networks, and software engineering, investigates topics such as algorithm optimization for HPC, the development of scalable cloud infrastructures, security in cloud computing environments, and the integration of cloud services with high-performance capabilities. The goal is to develop new approaches and technologies that fully leverage the large-scale processing capabilities of high-performance computing, along with the flexibility and accessibility of cloud computing, paving the way for innovations across various fields, from big data analysis to the modeling of complex systems.
More About the Coordinator
More About the Coordinator
Research Team
Previous Researchers
Current Projects
- Laguna Project - This project aims to extend the massive processing of a data lake using a cloud architecture, utilizing Amazon Web Services (AWS) as the provider.
Publications and Productions
Publications (6)
- NEUBERT, PATRICIA DA SILVA,CANTO, FÁBIOLORENSI DO,PINTO, ADILSON LUIZ,LIMA, Daniel Sundfeld,SILVA, FLÁVIO ROBERTO CRUZ, OpenAlex como fonte de dados para sistemas nacionais de informação científica: a experiência do projeto Laguna , in VII Workshop de Informação, Dados e Tecnologia WIDaT , 2024 . DOI: 10.22477/vii.widat.184 . Tags: High Performance Computing .
- CARVALHO SEGUNDO, WASHINGTON LUÍS RIBEIRO DE,CANTO, FABIO LORENSI DO,PINTO, ADILSON LUIZ,SUNDFELD, Daniel Lima, Atração entre periódicos brasileiros de medicina análise a partir de dados de citação do OpenAlex , in 9º Encontro Brasileiro de Bibliometria e Cientometria EBBC , 2024 . DOI: 10.22477/ix.ebbc.378 . Tags: High Performance Computing .
- FLAUSINO, CAIO GOMES,QUEIROZ, DIEGO CÉSAR FLORÊNCIO DE,Sundfeld, Daniel, LLC: Low Level Contêiner no Linux , 2023 . DOI: 10.5753/eradco.2023.234451 . Tags: High Performance Computing .
- DE OLIVEIRA, ENÉIAS PAULO,Sundfeld, Daniel, PA-Star-Web: web server para obtenção do alinhamento múltiplo ótimo de sequências biológicas , 2022 . DOI: 10.5753/erigo.2022.227676 . Tags: High Performance Computing .
- GOMES, RODRIGO ROCHA,Sundfeld, Daniel, CUDA-Sankoff-Web: Uma ferramenta web para cálculo do alinhamento secundário estrutural ótimo , in Escola Regional de Alto Desempenho de São Paulo , p25-28, 2021 . DOI: 10.5753/eradsp.2021.16697 . Tags: High Performance Computing .
- Sundfeld, Daniel,TEODORO, GEORGE,HAVGAARD, JAKOB H.,GORODKIN, JAN,Melo, Alba C. M. A., Using GPU to accelerate the pairwise structural RNA alignment with base pair probabilities , CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE , 32(e5468), 2020 . DOI: 10.1002/CPE.5468 . Tags: High Performance Computing .
Contact & Collaboration
- Email for information and contact with the team: daniel.sundfeld@unb.br
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High Performance Computing