PPT-SI2-SSE: Pipeline Framework for Ensemble Runs on the Cloud

Beth Plale PI Indiana University Craig Mattocks CoPI University of Miami Figure Scheduling tasks in Azure using Sigiri Middleware Climate change can have adverse impacts on strength of storms Even modest changes in Ocean surface temperature can have a significant impact on hurricane strength making the coastal regions increasingly vulnerable to storm surge . Boosting, Bagging, Random Forests and More. Yisong Yue. Supervised Learning. Goal:. learn predictor h(x) . High accuracy (low error). Using training data {(x. 1. ,y. 1. ),…,(. x. n. ,y. n. )}. Person. Data Considerations in the Cloud. Rob . Futrick. , CTO. We believe utility access to technical computing power . accelerates discovery & invention. The Innovation Bottleneck:. Scientists/Engineers . C. louds and TOA Radiation . B. udgets in the SMLs . U. sing NASA Satellite . O. bservations. Erica K. Dolinar. Xiquan. Dong and . Baike. Xi. University of North Dakota. This talk is based on . Dolinar. Beth . Plale. (PI), Indiana . University | Craig Mattocks (Co-PI), . University of Miami. . Goals:. . The goal of the project is to develop and/or assemble tooling to enable rapid and cost effective deployment of anywhere between 500 and 15,000 small jobs on cloud resources. This project develops a pipeline framework for running ensemble simulations on the cloud; the framework has two key components: . Scott Hunter. Principal Group Program Manager, App Plat. @. coolcsh. dotnetConf. Virtual . conference Microsoft/Community driven. July . 25-26: Microsoft . TBD 2014:. .NET Core (Compilers, Languages, Runtime). Bright, . Colle. , . DiMego. , Hacker, Whitaker. 22 Aug. 2012. DTC SAB ensemble task. 1. Primary recommendation. Continue to pursue long-term goal of pivotal and more tangible role in research-to-operations (R2O) transitions. . Jefferson Ridgeway. 2. , . Ifeanyi. . Rowland Onyenweaku. 3. , . Gregor. von Laszewski. 1*. , . Fugang. Wang. 1. 1*. Indiana University, Bloomington, IN 47408, U.S.A., . laszewski. @gmail.com. , . Kalman. Filter. Hans W. Chen, . Fuqing. Zhang, Thomas . Lauvaux. . and Kenneth J. Davis. Department of Meteorology and Atmospheric Science. The Pennsylvania State University. Surface CO. 2. fluxes are important to know to determine the atmospheric CO. Keith Dalbey, PhD. Sandia National Labs, Dept 1441. Optimization & Uncertainty Quantification. Abani. K. . Patra. , PhD. Department of Mechanical & Aerospace Engineering, University at Buffalo. Lifecycle. Workshop. Introductions, roles, and responsibilities. Microsoft Team. <CUSTOMERNAME> Team. Name. Title. Name. Title. Name. Title. Name. Title. Name. Title. Name. Title. Name. Title. Name. Srini Raghavan . Ali Rohani. BRK2077. What does it take to run high-quality real-time communications service globally? . How does the quality . of network . impact the quality of calls?. What are the right tools & approach to assess network readiness? . Zoli Herczeg. Evangelist. Microsoft Romania. zoli.herczeg@microsoft.com. http://zoli.herczeg.ro. *Inspired by Simon Guest’s ITS204 session @TechEd Europe 2009. This is Jim. Jim’s Boss (the CIO) has asked him to . for Cloud Computing and Big Data. Dept of CSE, PES University, Bangalore. Contact: Prof. . Dinkar. . Sitaram. , dinkars@pes.edu. Partially funded by EMC. Bursting across different deployments. Workload Migration Policies. Anya Greenberg. Pipeline - Things I Learned. Collect data from GEO database. Quality Control*. Differential Expression Gene Analysis*. Screen Potential Hub Genes. * not present in paper’s pipeline description.