Multiscale Modelling and Simulation, 11th International Workshop

Description: Modelling and simulation of multiscale systems constitutes a grand challenge in computational science, and is widely applied in fields ranging from the physical sciences and engineering to the life science and the socio-economic domain. Most of the real-life systems encompass interactions within and between a wide range of spatio-temporal scales, and/or on many separate levels of organization. They require the development of sophisticated models and computational techniques to accurately simulate the diversity and complexity of multiscale problems, and to effectively capture the wide range of relevant phenomena within these simulations. Additionally, these multiscale models frequently need large scale computing capabilities as well as dedicated software and services that enable the exploitation of existing and evolving computational eco systems. This workshop aims to provide a forum for multiscale application modellers, framework developers and experts from the distributed infrastructure communities to identify and discuss challenges in, and possible solutions for, modelling and simulating multiscale systems, as well as their execution on advanced computational resources. This workshop is a successor of the series of workshops on Simulation of Multiphysics Multiscale Systems organized over the last 10 years.

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5th Workshop on Computational Optimization, Modelling and Simulation (COMS2014)

Description: The 5th workshop on "Computational Optimization, Modelling and Simulation (COMS 2014)" will be a fifth event of the COMS workshop series at ICCS. COMS 2014 continues to provide a current forum and foster discussions on the cross-disciplinary research and development in computational optimization, computer modeling and simulations. COMS2014 will focus on new algorithms and methods, new trends, and latest developments in computational optimization, modelling and simulation as well as applications in science, engineering and industry.

Topics include (but not limited to): - Computational optimization, engineering optimization and design - Bio-inspired computing and algorithms - Metaheuristics (bat algorithm, cuckoo search, firefly algorithm, ABC, GA, PSO etc) - Simulation-driven design and optimization of computationally expensive objectives - Surrogate- and knowledge-based optimization algorithms - Scheduling and network optimization as well as design of experiements - Integrated approach to optimization and simulation - New optimization algorithms, modelling techniques related to optimization - Application case studies in engineering and industry.

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Fourth International Workshop on Advances in High-Performance Computational Earth Sciences: Applications and Frameworks

Description: High-performance computing is mandatory for simulations of complex physical phenomena on Earth. At the cross-road of rapid developments in several domains, geoscientists now see more necessities than ever for interactions between researchers on numerics, software, and hardware. This workshop thus aims to provide a forum for presentation and discussion of state-of-the-art research in high-performance computational earth sciences, by earth scientists, applied mathematicians, computational and computer scientists. Emphasis will be on novel advanced high-performance computational algorithms, formulations and simulations, as well as the related issues for computational environments and infrastructure.

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Agent-based simulations, adaptive algorithms and solvers

Description: The aim of workshop is to integrate results of different domains of computer science, computational science and mathematics. We invite papers oriented toward simulations, either hard simulations by means of finite element or finite difference methods, or soft simulations by means of evolutionary computations, particle swarm optimization etc. The workshop is most interested in simulations performed by using agent-oriented systems or adaptive algorithms, but simulations performed by other kind of systems are also welcome. This year we focus on Big Data aspect, e.g. agents based algorithms dealing with big data, model reduction techniques, fast solvers for large 3D simulations, etc.

Architecture, Languages, Compilation and Hardware support for Emerging ManYcore systems

Description: Massively parallel processors are made of hundreds to thousands cores, integrated memories and a dedicated network on a single chip. They provide high parallel performance while drastically reducing power consumption. Manycore architectures are therefore expected to enter both HPC (cloud servers, simulation, big data..) and embedded computing (autonomous vehicles, signal processing, cellular networks..). In the first session of this workshop, held together with ICCS 2013, we presented several academic and industrial works that contribute to the efficient programmability of manycores. This year, we also focus on preliminary user feedback to see if today available manycore processors meet their expectations.

Topics include, but are not limited to: * Advanced compilers for programming languages targeting massively parallel architectures * Advanced architecture support for massive parallelism management * Advanced architecture support for enhanced communication for CMP/manycores * Shared memory, data consistency models and protocols * New OS, or dedicated OS for massively parallel application * Runtime generation for parallel programing on manycores * User feedback on existing manycore architectures (experiments with Adapteva Epiphany, Intel Phi, Kalray MPPA, ST STHorm, Tilera Gx, TSAR..etc)

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Fifth Workshop on Data Mining in Earth System Science (DMESS 2014)

Description: Spanning many orders of magnitude in time and space scales, Earth science data are increasingly large and complex and often represent very long time series, making such data difficult to analyze, visualize, interpret, and understand. Moreover, advanced electronic data storage technologies have enabled the creation of large repositories of observational data, while modern high performance computing capacity has enabled the creation of detailed empirical and process-based models that produce copious output across all these time and space scales. The resulting "explosion" of heterogeneous, multi-disciplinary Earth science data have rendered traditional means of integration and analysis ineffective, necessitating the application of new analysis methods and the development of highly scalable software tools for synthesis, assimilation, comparison, and visualization. This workshop explores various data mining approaches to understanding Earth science processes, emphasizing the unique technological challenges associated with utilizing very large and long time series geospatial data sets. Especially encouraged are original research papers describing applications of statistical and data mining methods - including cluster analysis, empirical orthogonal functions (EOFs), genetic algorithms, neural networks, automated data assimilation, and other machine learning techniques - that support analysis and discovery in climate, water resources, geology, ecology, and environmental sciences research.

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Dynamic Data Driven Application Systems - DDDAS 2014

Description: This workshop covers several aspects of the Dynamic Data Driven Applications Systems (DDDAS) concept, which is an established approach defining a symbiotic relation between an application and sensor based measurement systems. Applications can accept and respond dynamically to new data injected into the executing application. In addition, applications can dynamically control the measurement processes. The synergistic feedback control-loop between an application simulation and its measurements opens new capabilities in simulations, e.g., the creation of applications with new and enhanced analysis and prediction capabilities, greater accuracy, longer simulations between restarts, and enable a new methodology for more efficient and effective measurements. DDDAS transforms the way science and engineering are done with a major impact in the way many functions in our society are conducted, e.g., manufacturing, commerce, transportation, hazard prediction and management, and medicine. The workshop will present such new opportunities as well as the challenges and approaches in technology needed to enable DDDAS capabilities in applications, relevant algorithms, and software systems. The workshop will showcase ongoing research in these aspects with examples from several important application areas. All related areas in Data-Driven Sciences are included in this workshop.

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8th Workshop on Computational Chemistry and Its Applications

Description: Computational chemistry uses computers in attempts to solve chemical problems. It uses theoretical methods implemented in software for computations. At the outset of the 21st Century, computational chemistry is leading to a wide range of possibilities usually interdisciplinary due to explosive increase in computer power and software capabilities. Computational chemistry is also integrating the chemistry curriculum. This workshop will provide the opportunity for researchers coming from corners of the world to be on a single platform for discussion, exchanging ideas and developing collaborations. This will be the eight workshop after being successful events in ICCS since 2003.

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Workshop on Teaching Computational Science

Description: The eighth Workshop on Teaching Computational Science (WTCS) solicits submissions describing innovations in teaching computational science in its various aspects (e.g. modeling and simulation, high-performance and large-data environments) at all levels and in all contexts. Typical topics include innovations in course content or curriculum structure, instructional methods or assessment, teaching or learning tools, alternative approaches, and non-academic training in computational sciences. These innovations may involve introductory programming, service courses, specialist undergraduate or postgraduate topics, industry-related short courses. We welcome submissions directed at issues of current and local importance, as well as topics of international interest.

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Tools for Program Development and Analysis in Computational Science

Description: The use of supercomputing technology, parallel and distributed processing, and sophisticated algorithms is of major importance for computational scientists. Yet, the scientists' goals are to solve their challenging scientific problems, not the software engineering tasks associated with it. For that reason, computational science and engineering must be able to rely on dedicated support from program development and analysis tools.

The primary intention of this workshop is to bring together developers of tools for scientific computing and their potential users. Paper submissions by both tool developers and users from the scientific and engineering community are encouraged in order to inspire communication between both groups. Tool developers can present to users how their tools support scientists and engineers during program development and analysis. Tool users are invited to report their experiences employing such tools, especially highlighting the benefits and the improvements possible by doing so.

The following areas and related topics are of interest: Problem solving environments for specific application domains Application building and software construction tools Domain-specific analysis tools Program visualization and visual programming tools On-line monitoring and computational steering tools Requirements for (new) tools emerging from the application domain

In addition, we encourage software tool developers to describe use cases and practical experiences of software tools for real-world applications in the following areas: Tools for parallel, distributed and network-based computing Testing and debugging tools Performance analysis and tuning tools (Dynamic) Instrumentation and monitoring tools Data (re-)partitioning and load-balancing tools Checkpointing and restart tools Tools for resource management, job queuing and accounting.

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Workshop on Cell Based and Individual Based Modelling

Description: Individual and cell based models are increasingly being used to study the behaviour of natural systems, from modelling individual cells to study tissue development through to representations of whole organisms to study population dynamics. The aim of this workshop is to bring together scientists who are developing and using individual based modelling tools and software.

The workshop will cover all aspects of model and tool development but will focus on the following. * Computational methods for the simulation and analysis of multicellular systems. * Standards for specification of multicellular systems. * Connecting individual based and continuum based modelling approaches. * Connecting models to experimental data.

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Solving Problems with Uncertainties

Description: Problems with uncertainty need to be tackled in an increasing variety of areas ranging from problems in physics, chemistry, computational biology to decision making in economics and social sciences. Uncertainty is unavoidable in almost all systems analysis, in risk analysis in decision making and economics and financial modeling, in weather and pollution modeling, disaster modeling and simulation, etc. With the advent of exascale computing larger and larger problems have to be tackled in a systematic way and the problem of solving such problems with uncertainties and quantifying the uncertainties becomes even more important due to the variety and scale of uncertainties in such problems. The focus of the workshop will be on methods and algorithms for solving problems with uncertainties, stochastic methods and algorithms for solving problems with uncertainty, methods and algorithms for quantifying uncertainties such as dealing with data input and missing data, sensitivity analysis (local and global), dealing with model inadequacy, model validation and averaging, software fault-tolerance and resilience, etc.

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2014 International Workshop on Software Engineering for Computational Science

Description: This workshop focuses on the use of Software Engineering (SE) practices in the development of Computational Science software. Specifically, :

- Scientific software applications, where the focus is on directly solving scientific problems, including but not limited to, large parallel models/simulations of the physical world (high performance computing systems).
- Applications that support scientific endeavors, including but not limited to, systems for managing and/or manipulating large amounts of data.

The importance of computational software motivates the need to identify and understand appropriate SE solutions that account for the salient characteristics of the computational environment.

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Modeling and Simulation of Large-scale Complex Urban Systems

Description: This workshop focuses on modeling and simulation of large-scale urban systems for planning and decision support. Submitted papers should examine urban processes from a complex systems perspective, including (but not limited to) methodologies such as agent-based modelling and complex networks. Application areas can include any form of urban system. For example, this includes transportation, human crowds, water, power, land use, etc. Work which investigates the interactions and interdependencies of different urban processes are of particular interest for this workshop. Papers related to simulation scaling and computational topics are also welcome. For example, this includes high-performance computing, multi-scale modelling, model interoperability and visualization.

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Urgent Computing: Computations for Decision Support in Critical Situations

Description: Decision support in critical situations comprising complex technical, environmental and social systems is a difficult interdisciplinary research area which is based on data-driven technologies, high-performance simulation and visualization facilities. The computational concept of urgent computing is considering as computational services (or resources) as data services work jointly in distributed environment for the help decision maker to make an optimal behavior scenario in time limitations.

The main topics of the workshop are: - Methods and the principles of urgent computing. - Urgent computing platforms and infrastructures. - Simulation-based decision support for complex systems. - Interactive visualization for decision support in emergency situations. - Domain-area applications to emergency situations, including natural disasters, transportation problems, epidemics, criminal acts, financial crisis etc.

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Large Scale Computational Physics

Description: The LSCP workshop will focus on symbolic and numerical methods and simulations, algorithms and tools (software and hardware) for developing and running large-scale computations in physical sciences. Special attention will go to parallelism, scalability and high numerical precision. System architectures are also of interest as long as they are supporting physics related calculations, such as: massively parallel systems, GPU, many-integrated-cores, distributed (cluster, grid/cloud) computing, and hybrid systems. Topics will be chosen from areas including: theoretical physics (high energy physics, nuclear physics, astrophysics, cosmology, quantum physics, accelerator physics), plasma physics, condensed matter physics, chemical physics, molecular dynamics, bio-physical system modeling, material science/engineering, nanotechnology, fluid dynamics, complex and turbulent systems, climate modeling.

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2nd Workshop on Advances in the Kepler Scientific Workflow System and Its Applications

Description: Kepler (kepler-project.org) is an open-source, cross-project collaboration to develop a scientific workflow system for multiple disciplines, providing a workflow environment for scientists, in which they can design and execute workflows. The Kepler Scientific Workflow System supports the design, execution, and management of scientific and engineering workflows through dedicated capabilities including provenance management, run management and reporting tools, integration of distributed computation and data management technologies, ability to ingest local and remote scripts, and sensor management and data streaming interfaces. The Kepler software is developed and maintained by the cross-project Kepler collaboration, which is led by a team consisting of several of the key institutions that originated the project. This workshop aims to bring researchers and developers contributing to Kepler together with informaticians and computational scientists using Kepler in order to communicate recent advances in Kepler and facilitate new development and collaborations.

The topics of interest for submission include, but are not limited to: * State-of-the-art Kepler application examples and success stories * Requirements from existing and potential Kepler communities * Big data science in Kepler * Best practices for using Kepler * Comparison of Kepler with other workflow systems * Kepler in educational environments * New developments and modules in Kepler

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The Eleventh Workshop on Computational Finance and Business Intelligence

Description: The workshop focus on computational science aspects of asset/derivatives pricing & financial risk management that relate to business intelligence. It will include but not limited to modeling, numeric computation, soft computing, algorithmic and complexity issues in arbitrage, asset pricing, future and option pricing, risk management, credit assessment, interest rate determination, insurance, foreign exchange rate forecasting, online auction, cooperative game theory, general equilibrium, information pricing, network band witch pricing, rational expectation, repeated games, etc. Accepted papers will be published in Elsevier Procedia. In addition, Green Futures, Inc., China has sponsored the workshop for "Green Future Award of Computational Finance and Business Intelligence" since ICCS 2008. An international award committee will select the awardees from the accepted and registered papers. Once a paper is selected, the author(s) are required to attend the workshop when the awards will be presented.

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Bridging the HPC Talent Gap with Computational Science Research Methods

Description: The workshop focuses on tackling the HPC talent Gap, which is similar, according to IDC and our latest studies, in EU, USA, Japan as well as in BRICS and Latin America. On the other hand we observe mathematics led innovation both in EU and USA, with critical demand of Computational Science Research Methods to bridge the above gap. Thus the focus of the workshop is on the overall environment and how the needed research skills for the changing HPC ecosystem can be built into the PG level and professional development. The intention is to provide forum for discussion highlighting not the single instances on lesson level but rather the means to affect change by increasing Computational Science visibility at curricula and degree level.

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Mathematical Methods and Algorithms for Extreme Scale

Description: Novel mathematics and mathematical modelling approaches together with scalable scientific algorithms are needed to enable key science applications at extreme-scale. This is especially true as HPC systems continue to scale up in compute node and processor core count. These extreme-scale systems require novel mathematical methods to be developd that lead to scalable scientific algorithms to hide network and memory latency, have very high computation/communication overlap, have minimal communication, have no synchronization points. The workshop seeks strategic and position papers in the above area and to serve as a forum for Computational Scientists to discuss the mathematical and algorithmic challenges and approaches towards exascale and beyond.

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Computational Optimisation in the Real World

Description: This workshop presents invited papers discussing design and application of optimisation algorithms to real problems in computational science. Emphasis is placed on algorithms and methods that are particularly suited to parallel computing environments, such as Grids, Clusters, GPGPU and Cloud Computing, due to the practical needs of many of the target problems. Applications of particular interest are those that illustrate the means taken for practical application to challenging problems: for example, problems of high dimensionality, multi- and many objectives, and complex fitness landscapes. Also of interest are descriptions of optimisation frameworks, particularly those allowing interaction and visual analysis.

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7th Workshop on Biomedical and Bioinformatics Challenges for Computer Science

Description: Emerging technologies in genomics, proteomics, interactomics and other life science areas are generating an increasing amount of complex data and information. The evolving data and information ecosystem includes large experimental "omics" data sets, natural language text from the scientific literature and the Web, and highly connected heterogeneous information networks, such as open linked data distributed on the Internet. Integrating and analysing this information in the context of modern life science research problems and biomedical applications poses a considerable challenge for bioinformatics and computational biology. Traditionally, bioinformatics has concentrated on methods and technologies facilitating the acquisition, storage, organization, archiving, analysis and visualization of biological and medical data. Computational biology, on the other, hand, has emphasized mathematical and computational techniques facilitating the modelling and simulation of biomedical processes and systems. In recent years the distinction between these two fields has become increasingly blurred. In order to tackle the growing complexity associated with emerging and future life science challenges, bioinformatics and computational biology researchers and developers need to explore, develop and apply novel computational concepts, methods, tools and systems. Many of these new approaches are likely to involve advanced and large-scale computing techniques, technologies and infrastructures.

Together, these topics cover the key bioinformatics and computational biology techniques and technologies encountered in modern life science environments: (1) Advanced computing architectures/infrastructures; (2) Data/information management and integration; (3) Data/information analysis and knowledge discovery; (4) Integration of quantitative/symbolic knowledge into executable biomedical "theories" or models. The aim of this workshop is to bring together computer and life scientists to discuss emerging and future directions in these areas.

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Research Computing Centre