A Search Space Exploration Framework for e-Science Applications

  • Eric B. Gauch IBM Research
  • Bruno E. C. Milanesi IBM Research
  • Bruno Silva IBM Research
  • Renato L. F. Cunha IBM Research
  • Marco A. S. Netto IBM Research

Resumo


High Performance Computing (HPC) has always been a fundamental component to conduct scientific experiments. Model calibrations/simulations often require several executions of scientific applications by changing their input parameters. This process is a common practice in research even though it represents a tedious and error-prone task. In this paper we propose Copper framework which employs a black-box strategy and contains a set of plugins to accelerate user experiments for exploring search spaces in HPC parametric applications. Copper has been used to conduct scientific experiments in different areas including, agriculture, oil gas, flood simulation, and bioinformatics.

Referências

Abramson, D., Giddy, J., and Kotler, L. (2000). High Performance Parametric Modeling with Nimrod/G: Killer Application for the Global Grid. In Proceedings of the 14th International Parallel & Distributed Processing Symposium. IEEE.

Anderson, D. P. (2004). BOINC: A system for public-resource computing and storage. In Proceedings of the 5th International Workshop on Grid Computing. IEEE.

Andrade, N., Cirne, W., Brasileiro, F., and Roisenberg, P. (2003). OurGrid: An approach to easily assemble grids with equitable resource sharing. In Proceeding of the Workshop on Job Scheduling Strategies for Parallel Processing. Springer.

Fedak, G., Germain, C., Néri, V., and Cappello, F. (2001). Xtremweb: A generic global computing system. In Proceedings of the 1st International Symposium on Cluster Computing and the Grid. IEEE.

Gil, Y., Ratnakar, V., Kim, J., Gonzalez-Calero, P., Groth, P., Moody, J., and Deelman, E. (2011). Wings: Intelligent workflow-based design of computational experiments. IEEE Intelligent Systems, 26(1):62–72.

Litzkow, M. J., Livny, M., and Mutka, M. W. (1988). Condor - A hunter of idle workstations. In Proceedings of the 8th International Conference on Distributed Computing Systems. IEEE.

Silva, B., Netto, M. A., and Cunha, R. L. (2018). JobPruner: A machine learning assistant for exploring parameter spaces in HPC applications. Future Generation Computer Systems, 83:144 – 157.

Silva, B., Netto, M. A. S., and Cunha, R. L. F. (2016). SLA-aware Interactive Workflow Assistant for HPC Parameter Sweeping Experiments. In Proceedings of the 11th Workshop on Workflows in Support of Large-Scale Science with The International Conference for High Performance Computing, Networking, Storage and Analysis.
Publicado
26/07/2018
GAUCH, Eric B.; MILANESI, Bruno E. C.; SILVA, Bruno; CUNHA, Renato L. F.; NETTO, Marco A. S.. A Search Space Exploration Framework for e-Science Applications. In: BRAZILIAN E-SCIENCE WORKSHOP (BRESCI), 12. , 2018, Natal. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2018 . p. 73-76. ISSN 2763-8774. DOI: https://doi.org/10.5753/bresci.2018.3276.