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PetaApps: Enabling Petascale Ensemble-based Data Assimilation for Numerical Analysis and Prediction of High-Impact Weather 

Sponsored by National Sciencie Foundation (OCI-0904938), 9/2009-8/2013



Xiaolin (Andy) Li (PI)

Graduate Students

Min Li
Rui Yang
Xin Yang
Ze Yu
Han Zhao


University of Oklahoma: M. Xue (PI), Henry Neeman (CoPI), Xuguang Wang (CoPI), Ronald Barnes  (CoPI)
Pittsburgh Supercomputing Center: S. Sanielevici (PI)

Project Summary

This project addresses the most challenging problems of very-high-resolution Numerical Weather Prediction, obtaining the optimal state estimations for initializing ensembles of predictions by assimilating the highest volume of weather observations available, and addressing problem sizes and scales that are only attainable on petascale computing platforms. An efficient and easy-to-use programming toolkit for a large class of weather forecasting applications will be developed.


  1. H. Zhao* and X. Li, "Designing Flexible Resource Rental Models for Implementing HPC-as-a-Service in Cloud," (accepted) PhD Forum for the 26th IEEE IPDPS 2012.
  2. H. Zhao*, M. Pan*, X. Liu*, X. Li, and Y. Fang, "Optimal Resource Rental Planning for Elastic Applications in Cloud Market," (accepted) the 26th IEEE International Parallel and Distributed Processing Symposium (IPDPS 2012). (Acceptance: 118/569 ~= 21%)
  3. H. Zhao*, X. Liu*, and X. Li, "Hypergraph-based Task-Bundle Scheduling Towards Efficiency and Fairness in Heterogeneous Distributed Systems," the 24th IEEE International Parallel and Distributed Processing Symposium (IPDPS 2010). (Acceptance: 127/527 ~= 24%)