Abstract: 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. This year following the challenges of ICCS 2015 theme "Computational Science at the Gates of Nature" we invite submissions using techniques dealing with large simulations, e.g. agents based algorithms dealing with big data, model reduction techniques for large problems, fast solvers for large three dimensional simulations, etc. To give - rather flexible - guidance in the subject, the following, more detailed, topics are suggested. These of theoretical brand, like: (a) multi-agent systems in high-performance computing, (b) efficient adaptive algorithms for big problems, (c) low computational cost adaptive solvers, (d) agent-oriented approach to adaptive algorithms, (e) model reduction techniques for large problems, (f) mathematical modeling and asymptotic analysis of large problems, (g) finite element or finite difference methods for three dimensional or non-stationary problems, (h) mathematical modeling and asymptotic analysis. And those with stress on application sphere: (a) agents based algorithms dealing with big data, (b) application of adaptive algorithms in large simulation, (c) simulation and large multi-agent systems, (d) application of adaptive algorithms in three dimensional finite element and finite difference simulations, (e) application of multi-agent systems in computational modeling, (f) multi-agent systems in integration of different approaches.

Abstract: In this work, we present a novel isogeometric analysis discretization for the Navier-Stokes-Cahn-Hilliard equation, which uses divergence-conforming spaces. Basis functions generated with this method can have higher-order continuity, and allow to directly discretize the higher-order operators present in the equation. The discretization is implemented in PetIGA-MF, a high-performance framework for discrete differential forms. We present solutions in a two-dimensional annulus, and model spinodal decomposition under shear flow.

Abstract: Cylindrical Petri dishes embedded in a rectangular waveguide and exposed to a polarized electromagnetic wave are often used to grow cell cultures. To guarantee the success of these cultures, it is necessary to enforce that the specific absorption rate distribution is sufficiently high and uniform over the Petri dish. Accurate numerical simulations are needed to design such systems. These simulations constitute a challenge due to the strong discontinuity of electromagnetic parameters of the materials involved, the relative low value of field within the dish cultures compared with the rest of the domain, and the presence of the meniscus shape developed at the liquid/solid interface. The latter greatly increases the level of complexity of the model in terms of geometry and the intensity of the gradients/singularities of the field solution. In here, we employ a three-dimensional (3D) $hp$-adaptive finite element method using isoparametric elements to obtain highly accurate simulations. We analyse the impact of the geometrical modeling of the meniscus shape cell culture in the $hp$-adaptivity. Numerical results concerning the convergence history of the error indicate the numerical difficulties arisen due to the presence of a meniscus-shaped object. At the same time, the resulting energy distribution shows that to consider such meniscus shape is essential to guarantee the success of the cell culture from the biological point of view.

Abstract: Scientific workflows in clouds have been successfully used for automation of large-scale computations, but so far they were applied to the loosely-coupled problems, where most workflow tasks can be processed independently in parallel and do not require high volume of communication. The multi-frontal solver algorithm for finite element meshes can be represented as a workflow, but the fine granularity of resulting tasks and the large communication to computation ratio makes it hard to execute it efficiently in loosely-coupled environments such as the Infrastructure-as-a-Service clouds. In this paper, we hypothesize that there exists a class of meshes that can be effectively decomposed into a workflow and mapped onto a cloud infrastructure. To show that, we have developed a workflow-based multi-frontal solver using the HyperFlow workflow engine, which comprises workflow generation from the elimination tree, analysis of the workflow structure, task aggregation based on estimated computation costs, and distributed execution using a~dedicated worker service that can be deployed in clouds or clusters. The results of our experiments using the workflows of over 10,000 tasks indicate that after task aggregation the resulting workflows of over 100 tasks can be efficiently executed and the overheads are not prohibitive. These results lead us to conclusions that our approach is feasible and gives prospects for providing a generic workflow-based solution using clouds for problems typically considered as requiring HPC infrastructure.

Abstract: We present an application of Ant Colony Optimisation (ACO) to simulate socio-cognitive features of a population. We incorporated perspective taking ability to generate three different proportions of ant colonies: Control Sample, High Altercentricity Sample, and Low Altercentricity Sample. We simulated their performances on the Travelling Salesman Problem and compared them with the classic ACO. Results show that all three 'cognitively enabled' ant colonies require less time than the classic ACO. Also, though the best solution is found by the classic ACO, the Control Sample finds almost as good a solution but much faster. This study is offered as an example to illustrate an easy way of defining inter-individual interactions based on stigmergic features of the environment.

Abstract: The objective of traditional goal-oriented strategies is to construct an optimal mesh that minimizes the problem size needed to achieve a user prescribed tolerance error for a given quantity of interest (QoI). Typical geophysical resistivity measurement acquisition systems can easily record electromagnetic (EM) fields. However, depending upon the application, EM fields are sometimes loosely related to the quantity that is to be inverted (conductivity or resistivity), and therefor they become inadequate for inversion. In the present work, we study the impact of the selection of the QoI in our inverse problem. We focus on two different acquisition systems: marine controlled source electromagnetic (CSEM), and magnetotellurics (MT). For both applications, numerical results illustrate the benefits of employing adequate QoI. Specifically, the use as QoI of the impedance matrix on MT measurements provides huge computational savings, since one can replace the existing absorbing boundary conditions (BCs) by a homogeneous Dirichlet BC to truncate the computational domain, something that is not possible when considering EM fields as QoI.

Abstract: We propose a multi-objective approach for solving challenging inverse parametric problems. The objectives are misfits for several physical descriptions of a phenomenon under consideration, whereas their domain is a common set of admissible parameters. The resulting Pareto set, or parameters close to it, constitute various alternatives of minimizing individual misfits. A special type of selection applied to the memetic solution of the multi-objective problem narrows the set of alternatives to the ones that are sufficiently coherent. The proposed strategy is exemplified by solving a real-world engineering problem consisting of the magnetotelluric measurement inversion that leads to identification of oil deposits located about 3 km under the Earth's surface, where two misfit functions are related to distinct frequencies of the electric and magnetic waves.

Abstract: In this paper we present the optimization of the energy consumption for the multi-frontal solver algorithm executed over two dimensional grids with point singularities. The multi-frontal solver algorithm is controlled by so-called elimination tree, defining the order of elimination of rows from particular frontal matrices, as well as order of memory transfers for Schur complement matrices. For a given mesh there are many possible elimination trees resulting in different number of floating point operations (FLOPs) of the solver or different amount of data transferred via memory transfers. In this paper we utilize the dynamic programming optimization procedure and we compare elimination trees optimized with respect to FLOPs with elimination trees optimized with respect to energy consumption.

Abstract: In this paper we analyze the optimality of the volume and neighbors algorithm constructing elimination trees for three dimensional h adaptive finite element method codes. The algorithm is a greedy algorithm that constructs the elimination trees based on the bottom up analysis of the computational mesh. We compare the results of the volume and neighbors greedy algorithm with the global dynamic programming optimization performed on a class of elimination trees. The comparison is based on the Directed Acyclic Graph (DAG) constructed for model grids. We construct DAGs for a two model grids, two dimensional grid with point singularity and two dimensional grid with edge singularity. We show that the quasi-optimal trees created by the volume and neighbors algorithm for considered grids are also captured by the dynamic programming procedure. It means that created elimination trees are optimal in the considered class of elimination trees. We show that different ordering of elements at the input of the volume and neighbors algorithm results in different computational costs of the multi-frontal solver algorithm executed over the resulting elimination trees. Finally we present the ordering of elements that results in optimal (in the considered class) elimination trees. The theoretical results are verified with numerical experiments performed on a three dimensional grids with point, edge and face singularities.

Abstract: In this paper we present a new integration scheme that can be applied for solution of dicult non-stationary problems. The scheme results from linearization of the Cranck-Nicolson scheme that is unconditionally stable but needs to solve non-linear equation at each time step. We test our linearized time integration scheme on the challenging Cahn-Hilliard equations, modeling the separation of two phase fluids. The problem is solved using higher order isogeometric fintie element method with B-spline basis functions. We implement our linear scheme in PETIGA framework interfaced via PETSc toolkit. We utilize a GMRES iterative solver for solution of a linear system at every time step. We also define a simple time adaptivity scheme, which increases the time step size when number of GMRES iterations is less than 30. We compare our linear scheme with simple time adaptation algorithm with non-linear scheme with sophisticated time adaptivity, on the two dimensional Cahn-Hilliard equations. We control the stability of our simulations by monitoring the Ginzberg-Landau free energy functional. We conclude that our simple scheme with simple time adaptivitiy outperforms the non-linear one with advanced time adaptivity by means of the execution time, while providing similar history of the evolution of the free energy functional.

Abstract: After a short introduction to the mathematical modelling of the elastic dynamic problem, which shows the similarity between the governing Partial Differential Equations (PDEs) in different applications, common blocks for Finite Element approximation are identified, and an Object Oriented Programming (OOP) methodology for linear and non-linear, stationary and dynamic problems is presented. Advantages of this approach are commented and some results are shown as examples of this methodology.

Abstract: Difficult black-box problems are required to be solved in many scientific and industrial areas. In this paper, efficient use of a hardware accelerator to implement dedicated solvers for such problems is discussed and studied based on an example of Golomb Ruler problem. The actual solution of the problem is shown based on evolutionary and memetic algorithms accelerated on GPGPU. The presented results prove the supremacy of GPGPU over optimized multicore CPU implementation.

Abstract: The problem of planning for groups of autonomous beings is gaining attention over the last few years. Real life tasks, like mobile robots coordination or urban traffic management, need robust and flexible solutions. In this paper a new approach to the problem of multi-variant planning in such systems is presented. It assumes use of simple reactive controllers by the beings, however the state observation is enriched by dynamically updated model, which contains planning results. The approach gives promising results in the considered use case, which is the Multi Robot Task Allocation problem.

Abstract: Graph transformations provide a well established method for the formal description of modifications of graph-based systems. On the other side such systems can be regarded as multi-agent ones providing a feasible mean for maintaining and manipulating large scale data. This paper deals with the problem of information exchange among agents maintaining different graph-based systems. Graph formalism applied for representing a knowledge maintained by agents is used at the same time to perform graph transformations modeling a knowledge exchange. The consistency of a knowledge represented by the set of agents is ensured by execution of some graph transformations rules by two agents in a parallel way. We suggest that complex operations (sequences of graph transformations) should be introduced instead of the formalism basing on simple unconditional operations. The approach presented in this paper is accompanied by examples concerning the problem of personal data distributed over different places (and maintained by different agents) and transmitted in such an environment\footnote{Financial support for this study was provided from resources of National Center for Research and Development, the grant number NCBiR 0021/R/ID2/2011/01. }.

Abstract: The paper contains the concept of agent-based search system and monitoring of Web pages. It is oriented at the exploration of limited problem area, covering a given sector of industry or economy. The proposal of agent-based (modular) structure of the system is due to the desire to ease the introduction of modifications or enrichment of its functionality. Commonly used search engines do not offer such a feature. The second part of the article presents a pilot version of the WEB mining system, representing a simplified implementation of the previously presented concept. Testing of the implemented application was executed by referring to the problem area of foundry industry.

Abstract: An agent-oriented software solution for simulation of marine unicellular organisms called foraminifera is presented. Their simplified microhabitat interactions are described and implemented to run the model and verify its flexibility. This group of well fossilizable protists has been selected due to its excellent ``in fossilio'' record that should help to verify our future long-run evolutionary results. The introduced system is built utilizing PyAge platform and based on easily exchangeable components that may be replaced (also in runtime). Selected experiments considering substantial and technological efficiency were conducted and the obtained results are presented and discussed.

Abstract: The article is an in-depth comparison of the solving process of the equation systems specific for finite difference, collocation and finite element methods. The paper considers recently developed isogeometric versions of the collocation and finite element methods, employing B-splines for the computations and ensuring C^{p-1} continuity on the borders of elements for the B-splines of the order p. For solving the systems, we use our GPU implementation of the state-of-the-art parallel multifrontal solver, which leverages modern GPU architectures and allows to reduce the complexity. We analyze the structures of linear equation systems resulting from each of the methods and how different structures of matrix lead to different multifrontal solver elimination trees. We also consider the flows of multifrontal solver depending on the originally employed method.