C+HPC Lab

Wordlwide strategic applications, such as those in the area of oil & gas, meteorology and biology, depend on high performance computing (High Performance Computing – HPC) to process large amounts of data. Cloud computing emerged as a low-cost alternative to HPC, offering a set of virtualized resources that can be quickly provisioned and dynamically scalable. The C+HPC Lab at UFF conducts research focusing on the problem of allocation and management of resources in clouds for the efficient and low cost execution of HPC applications, aiming to overcome the challenges that the use of this platform imposes to minimize the time of execution and energy consumption and to maximize fault tolerance, respecting service level agreements (SLA).

News

Doctoral Stay at Sorbonne

Ph.D. student Luan Teylo was awarded a six-month scholarship to pursue a doctoral stay at the Sorbonne Université in Paris. The scholarship is part of Capes PrInt’s ReMatCH project and started in September 2019, ending in February 2020. Luan Teylo is supervised by professor Lúcia Drummond and will work with professors Pierre Sens and Luciana …

winter school

PhD student Luan Teylo participated in the 5th GDR RSD and ASF Winter School on Distributed Systems and Networks. The winter school takes place annually in the French Alps region and is organized by GDR RSD and ACM SIGOPS, with support from INRIA. At the event, professors from different European universities share their academic experiences …

Publications

Journal and conference papers

    • SILVA JUNIOR, L. P. ; PAES, A. ; PACITTI, E. ; OLIVEIRA, D. . FReeP: towards parameter recommendation in scientific workflows using preference learning. In: XXXIII Simpósio Brasileiro de Banco de Dados, 2018, Rio de Janeiro. Anais do XXXIII Simpósio Brasileiro de Banco de Dados. Porto Alegre: Sociedade Brasileira de Computação, 2018.
    • VALDURIEZ, P. ; MATTOSO, M. ; AKBARINIA, R. ; BORGES, H. ; CAMATA, J. ; COUTINHO, A. ; GASPAR, D. ; LEMUS, N. ; LIU, J. ; LUSTOSA, H. ; MASSEGLIA, F. ; NOGUEIRA, F. ; SILVA, V. ; SOUZA, R. S. ; OCAÑA, K. ; OGASAWARA, E. ; OLIVEIRA, D. ; PACITTI, E. ; PORTO, F. ; SHASHA, D. . Scientific Data Analysis Using Data-Intensive Scalable Computing: the SciDISC Project . In: 1st LADaS – Latin American Data Science Workshop, 2018, Rio de Janeiro. Proceedings of the 1st LADaS – Latin American Data Science Workshop (in conjunction with VLDB’18), 2018.
    • FIGUEIREDO, ROSA ; Frota, Yuri ; LABBÉ, MARTINE . A branch-and-cut algorithm for the maximum -balanced subgraph of a signed graph. DISCRETE APPLIED MATHEMATICS, v. 1, p. 1-38, 2018.
    • PANTOJA, C. ; SOARES, H. D. ; VITERBO, J. ; SEGHROUCHNI, A. . An Architecture for th\e Development of Ambient Intelligence Systems Managed by Embedded Agents. In: International Conference on Software Engineering & Knowledge Engineering, 2018, São Francisco. Proceedings of the International Conference on Software Engineering and Knowledge Engineering 2018, 2018.
    • Guitierrez, J. L. V. ; Boeres, C. ; Rebello, V. E. F. . Combining VM Preemption Schemes to Improve Vertical Memory Elasticity Scheduling in Clouds. In: Proceedings of the 11th International Conference on Utility and Cloud Computing, Zurich, ACM, 2018. p. 53-62.
    • GUEDES, T.; JESUS A. L.; Ocaña, K. A.; DRUMMOND L. M.; OLIVEIRA, D. Provenance-based fault tolerance technique recommendationfor cloud-based scientific workflows: a practical approach. Cluster Computing, 2019.
    • CRUZ, R. A., BENTES, C., BREDER, B., VASCONCELLOS, E., CLUA, E., DE CARVALHO, P. M., & DRUMMOND, L. M. Maximizing the GPU resource usage by reordering concurrent kernels submission. Concurrency and Computation: Practice and Experience, 2018.
    • CARVALHO, P., CRUZ, R., DRUMMOND, L.M., BENTES, C., CLUA, E., CATALDO, E. & MARZULO, L.A.. Kernel concurrency opportunities based on GPU benchmarks characterization. Cluster Computing, pp.1-12, 2019.
    • TEOBALDO BULHÕES, RUSLAN SADYKOV, EDUARDO UCHOA. A branch-and-price algorithm for the Minimum Latency Problem.
      Computers & OR 93: 66-78(2018)
    • ARTUR ALVES PESSOA, RUSLAN SADYKOV, EDUARDO UCHOA. Enhanced Branch-Cut-and-Price algorithm for heterogeneous fleet vehicle routing problems. European Journal of Operational Research 270(2): 530-543 (2018)
    • ARTUR ALVES PESSOA, RUSLAN SADYKOV, EDUARDO UCHOA, FRANÇOIS VANDERBECK: Automation and Combination of Linear-Programming Based Stabilization Techniques in Column Generation. INFORMS Journal on Computing 30(2): 339-360 (2018)
    • BASTOS, I. V., MORAES, I. M., NGUYEN, T. M. T., PUJOLLE, G., “Modelo e Avaliação da Recuperação de Conteúdos Através de Funções de Rede Virtuais na Arquitetura de Computação na Borda em Redes Móveis”, em Simpósio Brasileiro de Redes de Computadores e de Sistemas Distribuídos (SBRC), 2019.
    • TEYLO, L., DRUMMOND, L., ARANTES, L., SENS, P., “Escalonamento de Aplicações em Instâncias Preemptivas Sujeitas a Falhas Temporais”, em XX WORKSHOP DE TESTES E TOLERÂNCIA A FALHAS (WTF), 2019.
    • TEYLO, L., ARANTES, L., SENS, P. AND DRUMMOND, L., “A Hibernation Aware Dynamic Scheduler for Cloud Environments”. In Proceedings of the 48th International Conference on Parallel Processing (ICPP): Workshops (p. 24). ACM, 2019.
    • TEYLO, L., ARANTES, L., SENS, P., DRUMMOND, L. “A Bag-of-Tasks Scheduler Tolerant to Temporal Failures in Clouds”. In The International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD). 2019.
    • HEIDSIECK, G. ; OLIVEIRA, D. ; PACITTI, E. ; PRADAL, C. ; TARDIEU, F. ; VALDURIEZ, P. . Adaptive Caching for Data-Intensive Scientific Workflows in the Cloud. In: 30th International Conference on Database and Expert Systems Applications, 2019, Linz, Austria. Proceedings of the 30th International Conference on Database and Expert Systems Applications, 2019.
    • HEIDSIECK, G. ; OLIVEIRA, D. ; PACITTI, E. ; PRADAL, C. ; TARDIEU, F. ; VALDURIEZ, P. . Efficient Execution of Scientific Workflows in the Cloud through Adaptive Caching. In: 35ème Conférence sur la Gestion de Données Principes, Technologies et Applications, 2019, Lyon, França. 35ème Conférence sur la Gestion de Données Principes, Technologies et Applications, 2019.
    • TEYLO, L., BRUM, R., ARANTES, L., SENS, P., DRUMMOND, L. “Avaliação dos Serviços de Armazenamento da Amazon Web Services para Gravação e Recuperação de Checkpoints” (WTF). 2020
    • CARVALHO P., DRUMMOND L.,  CLUA E.,  PAES A., BENTES C. and LOPES B.; ” Using Machine Learning Techniques to Analyze the Performance of Concurrent Kernel Execution on GPUs”. Future Generation Computer Systems (2020).

Books

  • de Oliveira, D. C. M., Liu, J., Pacitti, E. Data-Intensive Workflow Management: For Clouds and Data-Intensive and Scalable Computing Environments. Morgan & Claypool Publishers; 2019.

Contact

Instituto de Computação – UFF
Sala 403
Av. Gal. Milton Tavares de Souza, s/n
CEP 24210-310 – Niterói

Fone: +55 21 2629-2960