Data Driven Computational Sciences (DDCS) Session 1

Time and Date: 13:35 - 15:15 on 11th June 2018

Room: M6

Chair: Craig Douglas

394 Fast Retrieval of Weather Analogues in a Multi-petabytes Archive using Wavelet-based Fingerprints [abstract]
Abstract: Very large climate data repositories provide a consistent view of weather conditions over long time periods. In some applications and studies, given a current weather pattern (e.g. today's weather), it is useful to identify similar ones (weather analogues) in the past. Looking for simi-lar patterns in an archive using a brute force approach requires data to be retrieved from the ar-chive and the compared to the query, using a chosen similarity measure. Such operation would be very long and costly. In this work a wavelet-based fingerprinting scheme is proposed to in-dex all weather patterns from the archive. The scheme allows to answer queries by computing the fingerprint of the query pattern, then comparing them to the index of all fingerprints more ef-ficiently, in order to then retrieve only the corresponding selected data from the archive. The ex-perimental analysis is carried out on the ECMWF's ERA-Interim reanalyses data representing the global state of the atmosphere over seral decades. Results shows that 32 bits fingerprints are sufficient to represent metrological fields over a 1700 km×1700 km region and allow the quasi instantaneous retrieval of weather analogues.
Baudouin Raoult, Giuseppe Di Fatta, Florian Pappenberger and Bryan Lawrence
396 Assimilation of satellite detections and fire perimeters by minimization of the residual in a fire spread model [abstract]
Abstract: Assimilation of data into a fire-spread model is formulated as an optimization problem. The level set equation, which relates the fire arrival time and the rate of spread, is allowed to be satisfied only approximately, and we minimize a norm of the residual. Our previous methods based on modification of the fire arrival time either used an additive correction to the fire arrival time, or made a position correction. Unlike additive fire arrival time corrections, the new method respects the dependence of the fire rate of spread on diurnal changes of fuel moisture and on weather changes, and, unlike position corrections, it respects the dependence of the fire spread on fuels and terrain as well. The method is used to interpolate the fire arrival time between two perimeters by imposing the fire arrival time at the perimeters as constraints.
Angel Farguell Caus, James Haley, Adam Kochanski, Jan Mandel and Ana Cortes Fite
25 Analyzing Complex Models using Data and Statistics [abstract]
Abstract: Complex systems (e.g. volcanos, debris flows, climate) com- monly have many models advocated by different modelers and incorpo- rating different modeling assumptions. Limited and sparse data on the modeled phenomena does not permit a clean discrimination among mod- els for fitness of purpose and heuristic choices are usually made especially for critical predictions of behavior that has not been experienced. We advocate in recent work for characterizing models and the modeling as- sumptions they represent using a statistical approach over the full range of applicability of the models. Such a characterization may then be used to decide the appropriateness of a model for use and as needed weighted compositions of models for better predictive power. We use the example of dense granular representations of natural mass flows in volcanic debris avalanches to illustrate our approach.
Abani Patra
311 Research on Technology Foresight Method Based on Intelligent Convergence in Open Network Environment [abstract]
Abstract: With the development of technology, the technology foresight becomes more and more important. Delphi method as the core method of technology foresight is increasingly questioned. This paper propose a new technology foresight method based on intelligent convergence in open network environment. We put a large number of scientific and technological innovation topics into the open network technology community. Through the supervision and guidance to stimulate the discussion of expert groups, a lot of interactive information can be generated. Based on the accurate topic delivery, effective topic monitoring, reasonable topic guiding, comprehensive topic recovering, and interactive data mining, we get the technology foresight result and further look for the expert or team engaged in relevant research.
Minghui Zhao, Lingling Zhang, Libin Zhang and Feng Wang

Data Driven Computational Sciences (DDCS) Session 2

Time and Date: 15:45 - 17:25 on 11th June 2018

Room: M6

Chair: Craig Douglas

24 Bisections-weighted-by-element-size-and-order algorithm to optimize direct solver performance on 3D hp-adaptive grids. [abstract]
Abstract: The $hp$-adaptive Finite Element Method ($hp$-FEM) generates a sequence of adaptive grids with different polynomial orders of approximation and element sizes. The $hp$-FEM delivers exponential convergence of the numerical error with respect to the mesh size. In this paper, we propose a heuristic algorithm to construct element partition trees. The trees can be transformed directly into the orderings, which control the execution of the multi-frontal direct solvers during the $hp$ refined finite element method. In particular, the orderings determine the number of floating point operations performed by the solver. Thus, the quality of the orderings obtained from the element partition trees is important for good performance of the solver. Our heuristic algorithm has been implemented in three-dimensions and tested on a sequence of $hp$-refined meshes, generated during the $hp$ finite element method computations. We compare the quality of the orderings found by the heuristic algorithm to those generated by alternative state-of-the-art algorithms. We show 50 percent reduction in the number of flops and execution time.
Hassan Aboueisha, Victor Calo, Konrad Jopek, Mikhail Moshkov, Anna Paszynska and Maciej Paszynski
41 Establishing EDI for a Clinical Trial of a Treatment for Chikungunya [abstract]
Abstract: Ellagic acid (EA) is a polyphenolic compound with antiviral activity against Chikungunya, a rapidly spreading tropical disease transmitted to humans by mosquitoes. The most common symptoms of chikungunya virus infection are fe-ver and joint pain. Other manifestations of infection can include encephalitis and an arthritis-like joint swelling with pain that may persist for months or years after the initial infection. In 2014, there were 11 locally-transmitted cases of Chikungunya virus in the U.S., all reported in Florida. There is no approved vac-cine to prevent or medicine to treat Chikungunya virus infections. In this study, the Estimated Daily Intake (EDI) of EA from the food supply established using the National Health and Nutrition Examination Survey (NHANES) is used to set a maximum dose of an EA formulation for the clinical trial.
Robert Lodder, Mark Ensor and Cynthia Dickerson
283 Deadlock Detection in MPI Programs Using Static Analysis and Symbolic Execution [abstract]
Abstract: Parallel computing using MPI has become ubiquitous on multi-node computing clusters. A common problem while developing parallel codes is determining whether or not a deadlock condition can exist. Ideally we do not want to have to run a large number of examples to find deadlock conditions through trial and error procedures. In this paper we describe a methodology using both static analysis and symbolic execution of a MPI program to make a determination when it is possible. We note that using static analysis by itself is insufficient for realistic cases. Symbolic execution has the possibility of creating a nearly infinite number of logic branches to investigate. We provide a mechanism to limit the number of branches to something computable. We also provide examples and pointers to software necessary to test MPI programs.
Craig C. Douglas and Krishanthan Krishnamoorthy