PPT-Elastic-R , a collaborative and federative platform for scientific and statistical computing

Karim Chine karimchineclouderacouk Cloud Era Ltd Cambridge UK PRISM Forum Cloud Computing SIG Meeting 18 May 2010 lingua franca of data analysis From John Fox Aspects . cornelledu Abstract In scientific computing environments large amounts of floatingpoint data often need to be transferred between computers as well as to and from storage devices Compression can reduce the number of bits that need to be transferred a Aleksandra BUJNOWSKA . Eurostat. Statistical office of the European Union. Access to confidential data for scientific . purposes. Regulation (EC) No 223/2009 on European statistics defines . the basic principles of: . 1. A Framework for Effective. Multi-core Heterogeneous Computing. Introduction. 2. Clear trend towards multi-core heterogeneous systems. Problem: increased application-design complexity . Different resources require different algorithms to execute efficiently. IoT. and Analytics. Flavio Bonomi, Rodolfo . Milito. et al. prepared by Prashanth Peddabbu. Contents . Cloud computing. Fog computing. Need for Fog in . IoT. Why cloud computing is not enough?. Why end device computing is not enough?. Towards Integration of . IoT, People, and Clouds. WKO 5-5-2015, Wien. Schahram. . Dustdar. Distributed . Systems . Group. TU Vienna. dsg.tuwien.ac.at. Acknowledgements. NOTE: The . content. . includes. Background. NSF (DUE) funded grant on “Integrating Computing into the Statistics Curricula”. Goals:. map syllabi and sequences of courses for modern stat. programs . Facilitate instructors to introduce and teach such classes, providing resources (lecture notes, syllabi, assignments, data sets) and support network.. Li-Wen Chang. (a). , . Juan Gómez-Luna. (b). ,. . Izzat. El Hajj. (. a. ). , . Sitao. Huang. (. a. ). , Deming Chen. (a). , and Wen-Mei W. . Hwu. (a). (a). University of Illinois at Urbana-Champaign. Sources: D. Jensen. “Research Methods for Empirical Computer Science. .”. . Paul . R. . Cohen. . “Empirical . Methods for Artificial . Intelligence”. . Smithsonian Institute. . The Library of Congress. Cloud computing is a model for enabling . convenient. , . on-demand network access . to a . shared pool . of . configurable computing resources . (e.g., networks, servers, storage, applications, and services) [Mell_2009], [Berkely_2009]. . Computational Lab. Scott Sammons. Kevin Tang. Chandni Desai. Sequencing Lab. Mike Frace. Missy Olsen-Rasmussen. Marina Khristova. Lori Rowe. Pacific Biosciences SMRT sequencer. . Ion Torrent Personal Gene Machine. Cloud Computing. Cloud Computing . Characteristics . On demand service . . Use it as you needed. 2. Network Access . . Uses internet as a medium. 3. Share resources . Resources are pooled together – Used by multiple clients. Li-Wen Chang. (a). , . Juan Gómez-Luna. (b). ,. . Izzat. El Hajj. (. a. ). , . Sitao. Huang. (. a. ). , Deming Chen. (a). , and Wen-Mei W. . Hwu. (a). (a). University of Illinois at Urbana-Champaign. Yemi Adesanya. October 2016. v. 3.0. 2. About Yemi Adesanya…... In my previous life: CERN fellow and technical . student. 1. 8. . years at SLAC. BaBar computing. Object-Oriented frameworks for data analysis (C++, Java). Yemi AdesanyaOctober 2016v 302About Yemi AdesanyaIn my previous life CERN fellow and technical student18years at SLACBaBar computingObject-Oriented frameworks for data analysis C JavaMonitoring and vi