CSE15 Abstracts
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CSE15 Abstracts Abstracts are printed as submitted by the authors. Society for Industrial and Applied Mathematics 3600 Market Street, 6th Floor Philadelphia, PA 19104-2688 USA Telephone: +1-215-382-9800 Fax: +1-215-386-7999 Conference E-mail: [email protected] Conference web: www.siam.org/meetings/ Membership and Customer Service: 800-447-7426 (US & Canada) or +1-215-382-9800 (worldwide) CS15 Abstracts 1 IP1 to a strong earthquake. Graph Data Analytics at Scale: Opportunities and Challenges Shinobu Yoshimura The University of Tokyo The four Vs of Big Data necessitate fundamentally different [email protected] data analytics. A promising strategy toward understand- ing of a complex system’s dynamics and function aims to extract features and relationships between them and to an- IP4 alyze how their evolution causes different functional system Extreme-scale Multigrid in Space and Time responses. Discovery and forecasting of patterns in such feature graphs can provide insights about the vulnerability Multigrid methods are important techniques for efficiently of our nations energy infrastructure to disturbances, the solving huge linear systems and they have already been spread of a cyber-security attack, or the anomalies in in- shown to scale effectively on millions of cores. Future exas- ternode communication in high performance systems. This cale architectures will require solvers to exhibit even higher talk will present some opportunities and challenges in us- levels of concurrency (1B cores), minimize data movement, ing this strategy for computational science and engineering exploit machine heterogeneity, and demonstrate resilience applications. to faults. While considerable research and development remains to be done, multigrid approaches are ideal for ad- Nagiza Samatova dressing these challenges. In this talk, we will discuss ef- North Carolina State University forts to develop extreme-scale multigrid, including a new Oak Ridge National Laboratory parallel time integration approach that has the potential [email protected] for significant speedups over standard time stepping. Robert Falgout IP2 Center for Applied Scientific Computing Model Reduction - Trouble with Scales? Lawrence Livermore National Laboratory [email protected] Scientific and technological advances call for more and morecomplexmodelsaswellassystematicwaysofcomple- menting them by observational data. Despite the ever in- IP5 creasing computing capacity, ironically, the need for quan- Statistical and Computational Challenges of Con- tifiable model reduction concepts is also gaining increasing straining Greenhouse Gas Budgets importance in numerous application contexts. Examples are large scale design or online optimization tasks, uncer- Predicting future changes to the global carbon cycle (and tainty quantification or inversion problems some of which therefore climate) and quantifying anthropogenic emissions may only become feasible through employing reduced mod- of greenhouse gases (GHGs) both require an understand- els. Starting from a flow scenario with microscales this ing of net GHGs emissions and uptake across a variety of talk highlights several aspects of related model reduction spatial and temporal scales. This talk will explore some of strategies with particular focus on accuracy and stabil- the core scientific questions related to understanding GHG ity guarantees, presence of small scales, singular pertur- budgets through the lens of the statistical and computa- bations, and high dimensionality. We address some of the tional challenges that arise. The focus will be on the use key ingredients, revolving around error-residual relations, of atmospheric observations, and applications will include rate-optimality as a benchmark notion, adaptive or greedy the natural and anthropogenic components of the methane methods, separation of variables. The discussion is illus- and carbon dioxide budgets. The discussion will include is- trated by numerical examples. sues related to the solution of spatiotemporal inverse prob- lems, uncertainty quantification, data fusion, gap filling, Wolfgang Dahmen and issues of “big data” arising from the use of satellite RWTH Aachen observations. IGPM [email protected] Anna Michalak Carnegie Institution for Science Stanford, CA IP3 [email protected] Petascale Finite Element Simulation of Real Worlds Complex Structure with Billions DOFs Model IP6 Scaling Open Systems for Future Computational Leading supercomputers offer the computing power of Challenges petascale, and exascale systems are expected to be avail- able by the end of this decade. Supercomputers with more Computational models are changing rapidly, partially in than tens of thousands of computing nodes, each of which response to growing data size and advances in high- has many cores cause serious problems in practical finite performance computing. Open approaches are well suited element software. We have been developing an open source to this dynamic environment as they provide agile re- parallel finite element software known as ADVENTURE, sponses to complex, evolving code, and support the greater which enables very precise analyses of practical structures goal of ensuring reproducible science. This presentation and machines using over 100 million to billions DOFs mesh. introduces some open initiatives addressing big data and The basic parallel solution algorithms employed are the hi- HPC and the role that software architectures and processes erarchical domain decomposition method with balancing plays in advancing scientific computation. Also discussed domain decomposition as preconditioner. In this talk, I are emerging trends including competitive challenges and explain several key technologies and one practical applica- active publications that will likely play an important role tion, i.e. seismic response of nuclear power plant subjected in the creation, development and deployment of computa- 2 CS15 Abstracts tional software. technology trends that support accessing and understand- ing our data using intuitive, web-based and query-driven Will Schroeder interfaces are now the norm. In this talk, I will discuss Kitware, Inc. these trends and several freely available, open-source ap- [email protected] proaches that leverage them. IP7 James Ahrens Los Alamos National Laboratory A Calculus for the Optimal Quantification of Un- [email protected] certainties The past century has seen a steady increase in the need of estimating and predicting complex systems and making SP1 (possibly critical) decisions with limited information. With Celebrating 15 Years of SIAM CSE this purpose, this talk will describe the development of a form of calculus allowing for the (computational) manip- ulation of infinite dimensional information structures and There can be no doubt that SIAM CSE has been a big its application to the optimal quantification of uncertain- success! We examine the growth of CSE in SIAM, and ties in complex systems and the scientific computation of more broadly as a discipline, and look toward some of the optimal statistical estimators/models. Specific examples challenges and opportunities for the future. will be discussed to illustrate how this form of calculus could also be used to facilitate/guide the process of scien- Linda R. Petzold tific discovery. University of California, Santa Barbara [email protected] Houman Owhadi Applied Mathematics Caltech [email protected] CP1 Computational Molecular Engineering: An Emerg- ing Technology in Process Engineering IP8 The Power of Matrix and Tensor Decompositions Molecular modeling and simulation has become a powerful in Smart Patient Monitoring tool which can be applied to many physical processes and Accurate and automated extraction of clinically relevant properties of fluids on the molecular level. A shift in the information from patient recordings requires an ingenious accessible length and time scales due to massively parallel combination of adequate pretreatment of the data (e.g. high-performance computing has greatly increased its po- artefact removal), feature selection, pattern recognition, tential. The novel molecular dynamics code ls1 mardyn, decision support, up to their embedding into user-friendly which scales excellently on up to 146 000 cores, is pre- user interfaces. The underlying computational problems sented, highlighting the emergence of computational molec- can be solved by making use of matrix and tensor decom- ular engineering as a discipline. positions as building blocks of higher-level signal process- ing algorithms. A major challenge here is how to make Martin T. Horsch, Stephan Werth the mathematical decompositions “interpretable’ such that University of Kaiserslautern, Germany they reveal the underlying medically relevant information Laboratory of Engineering Thermodynamics and improve medical diagnosis. The application of these [email protected], [email protected] decompositions and their benefits will be illustrated in a variety of case studies, including epileptic seizure onset lo- Christoph Niethammer, Colin Glass calisation using adult and neonatal scalp EEG and Event- High Performance Computing Center Stuttgart, Germany related potential analysis during simultaneous EEG-fMRI [email protected], [email protected] acquisition. Wolfgang Eckhardt, Philipp Neumann Sabine Van Huffel Technische Universit¨at M¨unchen, Germany ESAT-SCD(SISTA) Department of Electrical Engineering Scientific Computing in Computer Science Katholieke Universiteit Leuven [email protected],