Registered Workshops

Thematic workshops organized by experts in a particular area constitute the core of the conference. The list of accepted workshops is below, click through for brief information and workshop web/contact addresses to follow to find full details.

  1. Advances in High-Performance Computational Earth Sciences: Applications and Frameworks
  2. Agent-Based Simulations, Adaptive Algorithms and Solvers
  3. Applications of Matrix Computational Methods in the Analysis of “Modern Data”
  4. Architecture, Languages, Compilation and Hardware support for Emerging ManYcore systems
  5. Biomedical and Bioinformatics Challenges for Computer Science
  6. Bridging the HPC Talent Gap with Computational Science Research Methods
  7. Computational Chemistry and Its Applications
  8. Computational Finance and Business Intelligence
  9. Computational Optimization, Modelling and Simulation
  10. Data-Driven Computational Sciences
  11. Environmental Computing Applications – State of the Art
  12. Large Scale Computational Physics
  13. Mathematical-Methods-and-Algorithms for Extreme Scale
  14. Multiscale Modelling and Simulation
  15. Simulations of Flow and Transport: Modeling, Algorithms and Computation
  16. Solving Problems with Uncertainties
  17. Teaching Computational Science
  18. Tools for Program Development and Analysis in Computational Science
  19. Urgent Computing

Advances in High-Performance Computational Earth Sciences: Applications and Frameworks – IHPCES 2017

Contact: Kengo Nakajima,
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.

Agent-Based Simulations, Adaptive Algorithms and Solvers – ABS-AAS 2017

Contact: Maciej Paszynski,
Description: The aim of this 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 and other. The workshop is most interested in simulations performed by using agent-oriented systems or by utilizing adaptive algorithms, but simulations performed by other kind of systems are also welcome. Agent-oriented system seems to be the attractive tool useful for numerous domains of applications. Adaptive algorithms allow significant decrease of the computational cost by utilizing computational resources on most important aspect of the problem.

Applications of Matrix Computational Methods in the Analysis of “Modern Data” – AMCMD 2017

Contact: Kourosh Modarresi,
Description: “Modern Data” has unique characteristics such as, extreme sparsity, high correlation, high dimensionality and massive size. Modern data is very prevalent in all different areas of science such as Medicine, Environment, Finance, Marketing, Vision, Imaging, Text, Web, etc. A
major difficulty is that many of the old methods that have been developed for analyzing data during the last decades cannot be applied on modern data. One distinct solution, to overcome this difficulty, is the application of matrix computation and factorization methods such as SVD (singular value decomposition), PCA (principal component analysis), and NMF (non- negative matrix factorization), without which the analysis of modern data is not possible. This workshop covers the application of matrix computational science techniques in dealing with Modern Data.

Architecture, Languages, Compilation and Hardware Support for Emerging ManYcore Systems – ALCHEMY 2017

Contact: Stephane Louise,
Description: Many-core systems are though to be the future of computing both in the large scale computing world and in the embedded processing world. However they convey a challenge for programmability. This workshop addresses all the questions and answers being at hardware level, or software level; proposed solutions and still open questions.

Biomedical and Bioinformatics Challenges for Computer Science – BBC 2017

Contact: Mario Cannataro,
Description: Emerging technologies in biomedicine and bioinformatics are generating an increasing amount of complex data. To tackle the growing complexity associated with emerging and future life science challenges, bioinformatics and computational biology researchers need to explore, develop and apply novel computational concepts, methods, and tools.
The aim of this workshop is to bring together computer science and life scientists to discuss emerging and future directions in topics related to key bioinformatics and computational biology techniques: (1) Advanced computing architectures; (2) Data management and integration; (3) Data analysis and knowledge discovery; (4) Integration of quantitative/symbolic knowledge into executable biomedical “theories” or models.

Bridging the HPC Talent Gap with Computational Science Research Methods – BRIDGE 2017

Contact: Nia Alexandrov,
Description: The workshop focuses on tackling the HPC and Data Science 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 and Data 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 and Big Data ecosystems 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 and Data Science visibility at curricula and degree level.

Computational Chemistry and Its Applications – CCA 2017

Contact: Ponnadurai Ramasami,
Description: Computational chemistry uses computers 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.
The objectives of this workshop are to highlight the latest scientific advances within the broad field of computational chemistry in academia, industry and society.
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. It will also be a suitable platform for researchers from different fields to meet so that ideas for new interdisciplinary research can emerge.
This will be the eleventh workshop after being successful events in ICCS since 2003.
This workshop will consider only original work and the submissions will be selected after peer reviewing.
The accepted full manuscripts will be published in Procedia Computer Science.

Computational Finance and Business Intelligence – CFBI 2017

Contact: Yong Shi,
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.

Computational Optimization, Modelling and Simulation – COMS 2017

Contact: Xin-She Yang,
Description: The 8th workshop “Computational Optimization, Modelling and Simulation (COMS 2017)” will be a part of the International Conference on Computational Science (ICCS 2017). This will be the 8th event of the COMS workshop series with the first held during ICCS 2010 in Amsterdam, the second held during ICCS2011 in Singapore, the third at ICCS2012 in USA, the fourth at ICCS2013 in Spain, the fifth at ICCS2014 in Australia, the sixth event in Iceland and the seventh event in the USA. COMS 2017 intends to provide a forum and foster discussion on the cross-disciplinary research and development in computational optimization, computer modelling and simulation.
COMS2017 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 (ant and bee algorithms, cuckoo search, firefly algorithm, genetic algorithms, PSO, simulated annealing etc);
Simulation-driven design and optimization of computationally expensive objectives;
Surrogate- and knowledge-based optimization algorithms;
Scheduling and network optimization;
Integrated approach to optimization and simulation;
Multiobjective optimization;
New optimization algorithms, modelling techniques related to optimization;
Design of experiments;
Application case studies in engineering and industry.

Data-Driven Computational Sciences – DDCS 2017

Contact: Craig C. Douglas,
Description: In the late 1960’s, simple data assimilation revolutionarily transformed science in fields based on satellite data. Both NASA and NCAR produced stunningly revolutionary applications. The oil and gas industry jumped on this concept in the early to mid 1970’s creating commercial data assimilation pipeline products by multiple vendors that were used in more than 165 countries in short order. This led to intelligent data assimilation being the normal way to operate a reservoir or pipeline networks by the 1990’s by all of the major oil producers. Since the early 2000’s, government grant agencies (e.g., the National Science Foundation) applied this concept to update numerous fields creating astonishing improvemnts in simulations that continue to this day in many application areas.

Environmental Computing Applications – State of the Art – ECA 2017

Contact: Matti Heikkurinen,
Description: This workshop focuses on advances in environmental computing (using advanced environmental modelling techniques to analyse data sources with a goal of producing actionable knowledge). The submitted papers can be case studies or present new approaches to environmental computing systems, including (but not limited to) multi-model and multi-data frameworks (including metadata approaches), scalability of the systems, socio-economic impact of environmental computing, data and model semantics and visualisation.

Large Scale Computational Physics – LSCP 2017

Contact: Elise De Doncker,
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 at- tention 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 dynam- ics, bio-physical system modeling, material science/engineering, nanotechnology, fluid dynamics, complex and turbulent systems, climate modeling.

Mathematical-Methods-and-Algorithms for Extreme Scale – MATH-EX 2017

Contact: Vassil Alexandrov,
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 developed 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 areas and to serve as a forum for Computational Scientists to discuss the mathematical and algorithmic challenges and approaches towards exascale and beyond.

Multiscale Modelling and Simulation – MMS 2017

Contact: Derek Groen,
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 and their validation against experimental data.

Simulations of Flow and Transport: Modeling, Algorithms and Computation – SOFTMAC 2017

Contact: Shuyu Sun,
Description: Modeling of flow and transport is an essential component of many scientific and engineering applications, with increased interests in recent years. Application areas vary widely, and include groundwater contamination, carbon sequestration, air pollution, petroleum exploration and recovery, weather prediction, drug delivery, material design, chemical separation processes, biological processes, and many others. However, accurate mathematical and numerical simulation of flow and transport remains a challenging topic from many aspects of physical modeling, numerical analysis and scientific computation. Mathematical models are usually expressed via nonlinear systems of partial differential equations, with possibly rough and discontinuous coefficients, whose solutions are often singular and discontinuous. An important step of a numerical solution procedure is to apply advanced discretization methods (e.g. finite elements, finite volumes, and finite differences) to the governing equations. Local mass conservation and compatibility of numerical schemes are often necessary to obtain physical meaningful solutions. Another important solution step is the design of fast and accurate solvers for the large-scale linear and nonlinear algebraic equation systems that result from discretization. Solution techniques of interest include multiscale algorithms, mesh adaptation, parallel algorithms and implementation, efficient splitting or decomposition schemes, and others.
The aim of this special issue is to bring together researchers in the aforementioned field to highlight the current developments both in theory and methods, to exchange the latest research ideas, and to promote further collaborations in the community. We invite original research articles as well as review articles describing the recent advances in mathematical modeling, computer simulation, numerical analysis, and other computational aspects of flow and transport phenomena of flow and transport. Potential topics include, but are not limited to:
(1) advanced numerical methods for the simulation of subsurface and surface flow and transport, and associated aspects such as discretization, gridding, upscaling, multiscale algorithms, optimization, data assimilation, uncertainty assessment, and high performance parallel and grid computing;
(2) spatial discretization schemes based on advanced finite element, finite volume, and finite different methods; schemes that preserve local mass conservation (such as mixed finite element methods and discontinuous Galerkin methods) are of particular interest;
(3) decomposition methods for improved efficiency and accuracy in treating flow and transport problems; decomposition methods for nonlinear differential equations and dynamical systems arising in flow and transport; temporal discretization schemes for flow and transport;
(4) a-priori and a-posteriori error estimates in discretizations and decompositions; numerical convergence study; adaptive algorithms and implementation;
(5) modeling and simulation of single-phase and multi-phase flow in porous media or in free space, and its applications to earth sciences and engineering;
(6) modeling and simulation of subsurface and surface transport and geochemistry, and its application to environmental sciences and engineering;
(7) computational thermodynamics of fluids, especially hydrocarbon and other oil reservoir fluids, and its interaction with flow and transport;
(8) computational modeling of flow and transport in other fields, such as geological flow/transport in crust and mantle, material flow in supply chain networks, separation processes in chemical engineering, information flow, biotransport, and intracellular protein trafficking, will also be considered.

Solving Problems with Uncertainties – SPU 2017

Contact: Vassil Alexandrov,
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 modelling, in weather and pollution modelling, disaster modelling and simulation (earthquake modelling, forest fires simulation etc.). How uncertainty is handled and quantified shapes the integrity of the analysis, and the correctness and credibility of the solution and the results. With the advent of exascale computing and Big Data tackling uncertainties in case of larger and larger problems in a systematic way 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…

Teaching Computational Science – WTCS 2017

Contact: Angela B. Shiflet,
Description: The eighth Workshop on Teaching Computational Science (WTCS 2017) solicits submissions that describe 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, but are not restricted to, innovations in the following areas:
– course content,
– curriculum structure,
– methods of instruction,
– methods of assessment,
– tools to aid in teaching or learning,
– evaluations of alternative approaches, and
– non-academic training in computational sciences
These innovations may be in the context of formal courses or self-directed learning; they may involve, for example, 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. Such topics may include transition from school to university, articulation between vocational and university education, quality management in teaching, teaching people from other cultures, attracting and retaining female students, and flexible learning.

Tools for Program Development and Analysis in Computational Science – Tools 2017

Contact: Andreas Knüpfer,
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
This workshop has been part of ICCS since 2001.

Urgent Computing – UC 2017

Contact: Alexander Boukhanovsky,
Description: Complex, large-scale, collaborative simulations are becoming more and more crucial for decision making in critical situations like floods, earthquakes, wildfires, terroristic attacks, epidemics, pandemics, instabilities in financial markets and similar. Very often they are run in almost real time. Urgent computing is a new interdisciplinary research area of computer science addressing algorithms, methods and tools enabling prioritized and immediate access to distributed, large compute and storage systems (computers, grids, clouds) for such emergency computations required for clever decision making. This type of simulation provides data to decision support systems enabling decision makers to choose an optimal behavior scenario in time limitations.