Scientific Data Analysis Using Data-Intensive Scalable Computing: the SciDISC Project

Autor: Valduriez, P., Mattoso, M., Akbarinia, R., Borges, H., Camata, J., Coutinho, A., Gaspar, D., Lemus, N., Liu, J., Lustosa, H., Masseglia, F., Silva, F. N. D., Silva, V., Souza, R., Ocaña, K., Eduardo Ogasawara, Oliveira, D. D., Pacitti, E., Porto, F., Shasha, D.

Publikováno v: Proceedings of the Latin America Data Science Workshop co-located with 44th International Conference on Very Large Data Bases (VLDB)
LADaS: Latin America Data Science Workshop
LADaS: Latin America Data Science Workshop, Aug 2018, Rio de Janeiro, Brazil
BASE-Bielefeld Academic Search Engine
Scopus-Elsevier
Kary Ocaña

International audience; Data-intensive science requires the integration of two fairly different paradigms: high-performance computing (HPC) and data-intensive scalable computing (DISC), as exemplified by frameworks such as Hadoop and Spark. In this c

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::2dc2ffde65b313bdf1c256cd53358b08
https://hal-lirmm.ccsd.cnrs.fr/lirmm-01867804/document