### ICCS 2015 Main Track (MT) Session 4

#### Chair: Sascha Hell

 411 Point Distribution Tensor Computation on Heterogeneous Systems [abstract]Abstract: Big data in observational and computational sciences impose increasing challenges on data analysis. In particular, data from light detection and ranging (LIDAR) measurements are questioning conventional methods of CPU-based algorithms due to their sheer size and complexity as needed for decent accuracy. These data describing terrains are natively given as big point clouds consisting of millions of independent coordinate locations from which meaningful geometrical information content needs to be extracted. The method of computing the point distribution tensor is a very promising approach, yielding good results to classify domains in a point cloud according to local neighborhood information. However, an existing KD-Tree parallel approach, provided by the VISH visualization framework, may very well take several days to deliver meaningful results on a real-world dataset. Here we present an optimized version based on uniform grids implemented in OpenCL that is able to deliver results of equal accuracy up to 24 times faster on the same hardware. The OpenCL version is also able to benefit from a heterogeneous environment and we analyzed and compared the performance on various CPU, GPU and accelerator hardware platforms. Finally, aware of the heterogeneous computing trend, we propose two low-complexity dynamic heuristics for the scheduling of independent dataset fragments in multi-device heterogenous systems. Ivan Grasso, Marcel Ritter, Biagio Cosenza, Werner Benger, Günter Hofstetter, Thomas Fahringer 465 Toward a multi-level parallel framework on GPU cluster with PetSC-CUDA for PDE-based Optical Flow computation [abstract]Abstract: In this work we present a multi-level parallel framework for the Optical Flow computation on a GPUs cluster, equipped with a scientific computing middleware (the PetSc library). Starting from a flow-driven isotropic method, which models the optical flow problem through a parabolic partial differential equation (PDE), we have designed a parallel algorithm and its software implementation that is suitable for heterogeneous computing environments (multiprocessor, single GPU and cluster of GPUs). The proposed software has been tested on real SAR images sequences. Experiments highlight the performances obtained and a gain of about 95% with respect to the sequential implementation. Salvatore Cuomo, Ardelio Galletti, Giulio Giunta, Livia Marcellino 472 Performance Analysis and Optimisation of Two-Sided Factorization Algorithms for Heterogeneous Platform [abstract]Abstract: Many applications, ranging from big data analytics to nanostructure designs, require the solution of large dense singular value decomposition (SVD) or eigenvalue problems. A first step in the solution methodology for these problems is the reduction of the matrix at hand to condensed form by two-sided orthogonal transformations. This step is standardly used to significantly accelerate the solution process. We present a performance analysis of the main two-sided factorizations used in these reductions: the bidiagonalization, tridiagonalization, and the upper Hessenberg factorizations on heterogeneous systems of multicore CPUs and Xeon Phi coprocessors. We derive a performance model and use it to guide the analysis and to evaluate performance. We develop optimized implementations for these methods that get up to $80\%$ of the optimal performance bounds. Finally, we describe the heterogeneous multicore and coprocessor development considerations and the techniques that enable us to achieve these high-performance results. The work here presents the first highly optimized implementation of these main factorizations for Xeon Phi coprocessors. Compared to the LAPACK versions optmized by Intel for Xeon Phi (in MKL), we achieve up to $50\%$ speedup. Khairul Kabir, Azzam Haidar, Stanimire Tomov, Jack Dongarra 483 High-Speed Exhaustive 3-locus Interaction Epistasis Analysis on FPGAs [abstract]Abstract: Epistasis, the interaction between genes, has become a major topic in molecular and quantitative genetics. It is believed that these interactions play a significant role in genetic variations causing complex diseases. Several algorithms have been employed to detect pairwise interactions in genome-wide association studies (GWAS) but revealing higher order interactions remains a computationally challenging task. State of the art tools are not able to perform exhaustive search for all three-locus interactions in reasonable time even for relatively small input datasets. In this paper we present how a hardware-assisted design can solve this problem and provide fast, efficient and exhaustive third-order epistasis analysis with up-to-date FPGA technology. Jan Christian Kässens, Lars Wienbrandt, Jorge González-Domínguez, Bertil Schmidt and Manfred Schimmler 487 Evaluating the Potential of Low Power Systems for Headphone-based Spatial Audio Applications [abstract]Abstract: Embedded architectures have been traditionally designed tailored to perform a dedicated (specialized) function, and in general feature a limited amount of processing resources as well as exhibit very low power consumption. In this line, the recent introduction of systems-on-chip (SoC) composed of low power multicore processors, combined with a small graphics accelerator (or GPU), presents a notable increment of the computational capacity while partially retaining the appealing low power consumption of embedded systems. This paper analyzes the potential of these new hardware systems to accelerate applications that integrate spatial information into an immersive audiovisual virtual environment or into video games. Concretely, our work discusses the implementation and performance evaluation of a headphone-based spatial audio application on the Jetson TK1 development kit, a board equipped with a SoC comprising a quad-core ARM processor and an NVIDIA "Kepler" GPU. Our implementations exploit the hardware parallelism of both types of architectures by carefully adapting the underlying numerical computations. The experimental results show that the accelerated application is able to move up to 300 sound sources simultaneously in real time on this platform. Jose A. Belloch, Alberto Gonzalez, Rafael Mayo, Antonio M. Vidal, Enrique S. Quintana-Orti

### ICCS 2015 Main Track (MT) Session 5

#### Chair: Lars Wienbrandt

 488 Real-Time Sound Source Localization on an Embedded GPU Using a Spherical Microphone Array [abstract]Abstract: Spherical microphone arrays are becoming increasingly important in acoustic signal processing systems for their applications in sound field analysis, beamforming, spatial audio, etc. The positioning of target and interfering sound sources is a crucial step in many of the above applications. Therefore, 3D sound source localization is a highly relevant topic in the acoustic signal processing field. However, spherical microphone arrays are usually composed of many microphones and running signal processing localization methods in real time is an important issue. Some works have already shown the potential of Graphic Processing Units (GPUs) for developing high-end real-time signal processing systems. New embedded systems with integrated GPU accelerators providing low power consumption are becoming increasingly relevant. These novel systems play a very important role in the new era of smartphones and tablets, opening further possibilities to the design of high-performance compact processing systems. This paper presents a 3D source localization system using a spherical microphone array fully implemented on an embedded GPU. The real-time capabilities of these platforms are analyzed, providing also a performance analysis of the localization system under different acoustic conditions. Jose A. Belloch, Maximo Cobos, Alberto Gonzalez, Enrique S. Quintana-Orti 81 The Scaled Boundary Finite Element Method for the Analysis of 3D Crack Interaction [abstract]Abstract: The Scaled Boundary Finite Element Method (SBFEM) can be applied to solve linear elliptic boundary value problems when a so-called scaling center can be defined such that every point on the boundary is \textit{visible} from it. From a more practical point of view, this means that in linear elasticity, a separation of variables ansatz can be used for the displacements in a scaled boundary coordinate system. This approach allows an analytical treatment of the problem in the scaling direction. Only the boundary needs to be discretized with Finite Elements. Employment of the separation of variables ansatz in the virtual work balance yields a Cauchy-Euler differential equation system of second order which can be transformed into an eigenvalue problem and solved by standard eigenvalue solvers for nonsymmetric matrices. A further obtained linear equation system serves for enforcing the boundary conditions. If the scaling center is located directly at a singular point, elliptic boundary value problems containing singularities can be solved with high accuracy and computational efficiency. The application of the SBFEM to the linear elasticity problem of two meeting inter-fiber cracks in a composite laminate exposed to a simple homogeneous temperature decrease reveals the presence of hypersingular stresses. Sascha Hell and Wilfried Becker 85 Algorithmic Differentiation of Numerical Methods: Second-Order Tangent Solvers for Systems of Parametrized Nonlinear Equations [abstract]Abstract: Forward mode algorithmic differentiation transforms implementations of multivariate vector functions as computer programs into first directional derivative (also: first-order tangent) code. Its reapplication yields higher directional derivative (higher-order tangent) code. Second derivatives play an important role in nonlinear programming. For example, second-order (Newtontype) nonlinear optimization methods promise faster convergence in the neighborhood of the minimum through taking into account second derivative information. Part of the objective function may be given implicitly as the solution of a system of n parameterized nonlinear equations. If the system parameters depend on the free variables of the objective, then second derivatives of the nonlinear system’s solution with respect to those parameters are required. The local computational overhead for the computation of second-order tangents of the solution vector with respect to the parameters by Algorithmic Differentiation depends on the number of iterations performed by the nonlinear solver. This dependence can be eliminated by taking a second-order symbolic approach to differentiation of the nonlinear system. Niloofar Safiran, Johannes Lotz, Uwe Naumann

### ICCS 2015 Main Track (MT) Session 8

#### Room: M101

 469 Expressively Modeling the Social Golfer Problem in SAT [abstract]Abstract: Constraint Satisfaction Problems allow one to expressively model problems. On the other hand, propositional satisfiability problem (SAT) solvers can handle huge SAT instances. We thus present a technique to expressively model set constraint problems and to encode them automatically into SAT instances. Our technique is expressive and less error-prone. We apply it to the Social Golfer Problem and to symmetry breaking of the problem. Frederic Lardeux, Eric Monfroy 538 Multi-Objective Genetic Algorithm for Variable Selection in Multivariate Classication Problems: A Case Study in Verification of Biodiesel Adulteration [abstract]Abstract: This paper proposes multi-objective genetic algorithm for the problem of variable selection in multivariate calibration. We consider the problem related to the classification of biodiesel samples to detect adulteration, Linear Discriminant Analysis classifier. The goal of the multi-objective algorithm is to reduce the dimensionality of the original set of variables; thus, the classification model can be less sensitive, providing a better generalization capacity. In particular, in this paper we adopted a version of the Non-dominated Sorting Genetic Algorithm (NSGA-II) and compare it to a mono-objective Genetic Algorithm (GA) in terms of sensitivity in the presence of noise. Results show that the mono-objective selects 20 variables on average and presents an error rate of 14%. One the other hand, the multi-objective selects 7 variables and has an error rate of 11%. Consequently, we show that the multi-objective formulation provides classification models with lower sensitivity to the instrumental noise when compared to the mono-objetive formulation. Lucas de Almeida Ribeiro, Anderson Da Silva Soares 653 Sitting Multiple Observers for Maximum Coverage: An Accurate Approach [abstract]Abstract: The selection of the lowest number of observers that ensures the maximum visual coverage over an area represented by a digital elevation model (DEM) is an important problem with great interest in many elds, e.g., telecommunications, environment planning, among others. However, this problem is complex and intractable when the number of points of the DEM is relatively high. This complexity is due to three issues: 1) the diculty in determining the visibility of the territory from a point, 2) the need to know the visibility at all points of the territory and 3) the combinatorial complexity of the selection of observers. The recent progress in total-viewshed maps computation not only provides an ecient solu-tion to the rst two problems, but also opens other ways to new solutions that were unthinkable previously. This paper presents a new type of cartography, called the masked total viewshed map, and based on this algorithm, optimal solutions for both sequential and simultaneous observers location are provided. Antonio Manuel Rodriguez Cervilla, Siham Tabik, Luis Felipe Romero Gómez 169 USING CRITERIA RECONSTRUCTION OF LOW-SAMPLING TRAJECTORIES AS A TOOL FOR ANALYTICS [abstract]Abstract: Today, a lot of applications with incorporated Geo Positional Systems (GPS) deliver huge quantities of spatio-temporal data. Trajectories followed by moving objects can be generated from this data. However, these trajectories may have silent durations, i.e., time durations when no data are available for describing the route of a MO. As a result, the movement during silent durations must be described and the low sampling data trajectory need to be filled in using specialized techniques of data imputation to study and discover new knowledge based on movement. Our interest is to show opportunities of analytical tasks using a criteria based operator over reconstructed low-sampling trajectories. Also, a simple visual analysis of the reconstructed trajectories is done to offer a simple analytic perspective of the reconstruction and how the criterion of movement can change the analysis. To the best of our knowledge, this work is the first attempt to use the different reconstruction of trajectories criteria to identify the opportunities of analytical tasks over reconstructed low-sampling trajectories as a whole. Francisco Moreno, Edison Ospina, Iván Amón Uribe 258 Using Genetic Algorithms for Maximizing Technical Efficiency in Data Envelopment Analysis [abstract]Abstract: Data Envelopment Analysis (DEA) is a non-parametric technique for estimating the technical efficiency of a set of Decision Making Units (DMUs) from a database consisting of inputs and outputs. This paper studies DEA models based on maximizing technical efficiency, which aim to determine the least distance from the evaluated DMU to the production frontier. Usually, these models have been solved through unsatisfactory methods used for combinatorial NP-hard problems. Here, the problem is approached by metaheuristic techniques and the solutions are compared with those of the methodology based on the determination of all the facets of the frontier in DEA. The use of metaheuristics provides solutions close to the optimum with low execution time. Martin Gonzalez, Jose J. Lopez-Espin, Juan Aparicio, Domingo Gimenez, Jesus T. Pastor

### ICCS 2015 Main Track (MT) Session 11

#### Chair: Emilio Luque

 379 Towards a Cognitive Agent-Based Model for Air Conditioners Purchasing Prediction [abstract]Abstract: Climate change as a result of human activities is a problem of a paramount importance. The global temperature on Earth is gradually increasing and it may lead to substantially hotter summers in a moderate belt of Europe, which in turn is likely to influence the air conditioning penetration in this region. The current work is an attempt to predict air conditioning penetration in different residential areas in the UK between 2030-2090 using an integration of calibrated building models, future weather predictions and an agent-based model. Simulation results suggest that up to 12% of homes would install an air conditioner in 75 years’ time assuming an average purchasing ability of the households. The performed simulations provide more insight into the influence of overheating intensity along with households’ purchasing ability and social norms upon households’ decisions to purchase an air conditioner. Nataliya Mogles, Alfonso Ramallo-González, Elizabeth Gabe-Thomas 481 Crowd evacuations SaaS: an ABM approach [abstract]Abstract: Crowd evacuations involve thousands of persons in closed spaces. Having knowledge about where the problematic exits will be or where the disaster may occur can be crucial in emergency planning. We implemented a simulator using Agent Based Modelling able to model the behaviour of people in evacuation situations and a workflow able to run it in the cloud. The input is just a PNG image and the output are statistical results of the simulation executed on the cloud. This allows to provide the user with a system abstraction and only a map of the scenario is needed. Many events are held in main city squares, so to test our system we chose Siena and we fit about 28,000 individuals in the centre of the square. The software has special computational requirements because the results need to be statistically reliable. Because these needs we use distributed computing. In this paper we show how the simulator scales efficiently on the cloud. Albert Gutierrez-Milla, Francisco Borges, Remo Suppi, Emilio Luque 499 Differential Evolution with Sensitivity Analysis and the Powell's Method for Crowd Model Calibration [abstract]Abstract: Evolutionary algorithms (EAs) are popular and powerful approaches for model calibration. This paper proposes an enhanced EA-based model calibration method, namely the differential evolution (DE) with sensitivity analysis and the Powell's method (DESAP). In contrast to traditional EA-based model calibration methods, the proposed DESAP owns three main features. First, an entropy-based sensitivity analysis operation is integrated so as to dynamically identify important parameters of the model as evolution progresses online. Second, the Powell's method is performed periodically to fine-tune the important parameters of the best individual in the population. Finally, in each generation, the DE operators are performed on a small number of better individuals rather than all individuals in the population. These new search mechanisms are integrated into the DE framework so as to reduce the computational cost and to improve the search efficiency. To validate its effectiveness, the proposed DESAP is applied to two crowd model calibration cases. The results demonstrate that the proposed DESAP outperforms several state-of-the-art model calibration methods in terms of accuracy and efficiency. Jinghui Zhong and Wentong Cai 525 Strip Partitioning for Ant Colony Parallel and Distributed Discrete-Event Simulation [abstract]Abstract: Data partitioning is one of the main problems in parallel and distributed simulation. Distribution of data over the architecture directly influences the efficiency of the simulation. The partitioning strategy becomes a complex problem because it depends on several factors. In an Individual-oriented Model, for example, the partitioning is related to interactions between the individual and the environment. Therefore, parallel and distributed simulation should dynamically enable the interchange of the partitioning strategy in order to choose the most appropriate partitioning strategy for a specific context. In this paper, we propose a strip partitioning strategy to a spatially dependent problem in Individual-oriented Model applications. This strategy avoids sharing resources, and, as a result, it decreases communication volume among the processes. In addition, we develop an objective function that calculates the best partitioning for a specific configuration and gives the computing cost of each partition, allowing for a computing balance through a mapping policy. The results obtained are supported by statistical analysis and experimentation with an Ant Colony application. As a main contribution, we developed a solution where the partitioning strategy can be chosen dynamically and always returns the lowest total execution time. Francisco Borges, Albert Gutierrez-Milla, Remo Suppi, Emilio Luque 530 Model of Collaborative UAV Swarm Toward Coordination and Control Mechanisms Study [abstract]Abstract: In recent years, thanks to the low cost of deploying, maintaining an Unmanned Aerial Vehicle (UAV) system and the possibility to operating them in areas inaccessible or dangerous for human pilots, UAVs have attracted much research attention both in the military field and civilian application. In order to deal with more sophisticated tasks, such as searching survival points, multiple target monitoring and tracking, the application of UAV swarms is forseen. This requires more complex control, communication and coordination mechanisms. However, these mechanisms are difficult to test and analyze under flight dynamic conditions. These multi- UAV scenarios are by their nature well suited to be modeled and simulated as multi-agent systems. The first step of modeling an multi-agent system is to construct the model of agent, namely accurate model to represent its behavior, constraints and uncertainties of UAVs. In this paper we introduce our approach to model an UAV as an agent in terms of multi-agent system principle. Construction of the model to satisfy the need for a simulation environment that researchers can use to evaluate and analyze swarm control mechanisms. Simulations results of a case study is provided to demonstrate one possible use of this approach. Xueping Zhu, Zhengchun Liu, Jun Yang

### ICCS 2015 Main Track (MT) Session 13

#### Chair: Witold Dzwinel

 712 Collaborative Knowledge Fusion by Ad-Hoc Information Distribution in Crowds [abstract]Abstract: We study situations where (such as in a city festival) in the case of a phone signal outage cell phones can communicate opportunistically (for instance, using WiFi or Bluetooth) and we want to understand and control information spreading. A particular question is, how to prevent false information from spreading, and how to facilitate the spreading of useful (true) information? We introduce collaborative knowledge fusion as the operation by which individual, local knowledge claims are merged". Such fusion events are local, e.g. happen upon the physical meetings of knowledge providers. We study and evaluate different methods for collaborative knowledge fusion and study the conditions for and tradeoffs of the convergence to a global true knowledge state under various conditions. George Kampis, Paul Lukowicz 220 Modeling Deflagration in Energetic Materials using the Uintah Computational Framework [abstract]Abstract: Predictive computer simulations of large-scale deflagration and detonation are dependent on the availability of robust reaction models embedded in a computational framework capable of running on massively parallel computer architectures. We have been developing such models in the Uintah Computational Framework, which is capable of scaling up to 512k cores. Our particular interest is in predicting DDT for accident scenarios involving large numbers of energetic devices; the 2005 truck explosion in Spanish Fork Canyon, UT is a prototypical example. Our current reaction model adapts components from Ward, Son and Brewster to describe the effects of pressure and initial temperature on deflagration, from Berghout et al. for burning in cracks in damaged explosives, and from Souers for describing fully developed detonation. The reaction model has been subjected to extensive validation against experimental tests. Current efforts are focused on effects of carrying the computational grid elements on multiple aspects of deflagration and the transition to detonation. Jacqueline Beckvermit, Todd Harman, Andrew Bezdjian, Charles Wight 237 Fast Equilibration of Coarse-Grained Polymeric Liquids [abstract]Abstract: The study of macromolecular systems may require large computer simulations that are too time consuming and resource intensive to execute in full atomic detail. The integral equation coarse-graining approach by Guenza and co-workers enables the exploration of longer time and spatial scales without sacrificing thermodynamic consistency, by approximating collections of atoms using analytically-derived soft-sphere potentials. Because coarse-grained (CG) characterizations evolve polymer systems far more efficiently than the corresponding united atom (UA) descriptions, we can feasibly equilibrate a CG system to a reasonable geometry, then transform back to the UA description for a more complete equilibration. Automating the transformation between the two different representations simultaneously exploits CG efficiency and UA accuracy. By iteratively mapping back and forth between CG and UA, we can quickly guide the simulation towards a configuration that would have taken many more time steps within the UA representation alone. Accomplishing this feat requires a diligent workflow for managing input/output coordinate data between the different steps, deriving the potential at runtime, and inspecting convergence. In this paper, we present a lightweight workflow environment that accomplishes such fast equilibration without user intervention. The workflow supports automated mapping between the CG and UA descriptions in an iterative, scalable, and customizable manner. We describe this technique, examine its feasibility, and analyze its correctness. David Ozog, Jay McCarty, Grant Gossett, Allen Malony and Marina Guenza 392 Massively Parallel Simulations of Hemodynamics in the Human Vasculature [abstract]Abstract: We present a computational model of three-dimensional and unsteady hemodynamics within the primary large arteries in the human on 1,572,864 cores of the IBM Blue Gene/Q. Models of large regions of the circulatory system are needed to study the impact of local factors on global hemodynamics and to inform next generation drug delivery mechanisms. The HARVEY code successfully addresses key challenges that can hinder effective solution of image-based hemodynamics on contemporary supercomputers, such as limited memory capacity and bandwidth, flexible load balancing, and scalability. This work is the first demonstration of large (> 500 cm) fluid dynamics simulations of the circulatory system modeled at resolutions as high as 10 μm. Amanda Randles, Erik W. Draeger and Peter E. Bailey 402 Parallel performance of an IB-LBM suspension simulation framework [abstract]Abstract: We present performance results from ficsion, a general purpose parallel suspension solver, employing the Immersed-Boundary lattice-Boltzmann method (IB-LBM). ficsion is build on top of the open-source LBM framework Palabos, making use of its data structures and their inherent parallelism. We describe in brief the implementation and present weak and strong scaling results for simulations of dense red blood cell suspensions. Despite its complexity the simulations demonstrate a fairly good, close to linear scaling, both in the weak and strong scaling scenarios. Lampros Mountrakis, Eric Lorenz, Orestis Malaspinas, Saad Alowayyed, Bastien Chopard and Alfons G. Hoekstra

### ICCS 2015 Main Track (MT) Session 14

#### Chair: Lampros Mountrakis

 405 A New Stochastic Cellular Automata Model for Traffic Flow Simulation with Driver's Behavior Prediction [abstract]Abstract: In this work we introduce a novel, flexible and robust traffic flow cellular automata model. Our proposal includes two important stages that make possible the consideration of different profiles of drivers' behaviors. We first consider the motion expectation of cars that are in front of each driver. Secondly, we define how a specific car decides to get around, considering the foreground traffic configuration. Our model uses stochastic rules for both situations, adjusting the Probability Density Function of the Beta Distribution for three neighborhoods drives behavior, adjusting different parameters of the Beta distribution for each one. Marcelo Zamith, Leal-Toledo Regina, Esteban Clua, Elson Toledo and Guilherme Magalhães 557 A Model Driven Approach to Water Resource Analysis based on Formal Methods and Model Transformation [abstract]Abstract: Several frameworks have been proposed in literature in order to cope with critical infrastructure modelling issues, and almost all rely on simulation techniques. Anyway simulation is not enough for critical systems, where any problem may lead to consistent loss in money and even human lives. Formal methods are widely used in order to enact exhaustive analyses of these systems, but their complexity grows with system dimension and heterogeneity. In addition, experts in application domains could not be familiar with formal modelling techniques. A way to manage complexity of analysis is the use of Model Based Transformation techniques: analysts can express their models in the way they use to do and automatic algorithms translate original models into analysable ones, reducing analysis complexity in a completely transparent way. In this work we describe an automatic transformation algorithm generating hybrid automata for the analysis of a natural water supply system. We use real system located in the South of Italy as case study. Francesco Moscato, Flora Amato, Francesco De Paola, Crescenzo Diomaiuta, Nicola Mazzocca, Maurizio Giugni 175 An Invariant Framework for Conducting Reproducible Computational Science [abstract]Abstract: Computational reproducibility depends on being able to isolate necessary and sufficient computational artifacts and preserve them for later re-execution. Both isolation and preservation of artifacts can be challenging due to the complexity of existing software and systems and the resulting implicit dependencies, resource distribution, and shifting compatibility of systems as time progresses---all conspiring to break the reproducibility of an application. Sandboxing is a technique that has been used extensively in OS environments for isolation of computational artifacts. Several tools were proposed recently that employ sandboxing as a mechanism to ensure reproducibility. However, none of these tools preserve the sandboxed application for re-distribution to a larger scientific community---aspects that are equally crucial for ensuring reproducibility as sandboxing itself. In this paper, we describe a combined sandboxing and preservation framework, which is efficient, invariant and practical for large-scale reproducibility. We present case studies of complex high energy physics applications and show how the framework can be useful for sandboxing, preserving and distributing applications. We report on the completeness, performance, and efficiency of the framework, and suggest possible standardization approaches. Haiyan Meng, Rupa Kommineni, Quan Pham, Robert Gardner, Tanu Malik and Douglas Thain 264 Very fast interactive visualization of large sets of high-dimensional data [abstract]Abstract: The embedding of high-dimensional data into 2D (or 3D) space is the most popular way of data visualization. Despite recent advances in developing of very accurate dimensionality reduction algorithms, such as BH-SNE, Q-SNE and LoCH, their relatively high computational complexity still remains the obstacle for interactive visualization of truly large sets of high-dimensional data. We show that a new clone of the multidimensional scaling method (MDS) – nr-MDS – can be up to two orders of magnitude faster than the modern dimensionality reduction algorithms. We postulate its linear O(M) computational and memory complexity. Simultaneously, our method preserves in 2D and 3D target spaces high separability of data, similar to that obtained by the state-of-the-art dimensionality reduction algorithms. We present the effects of nr-MDS application in visualization of data repositories such as 20 Newsgroups (M=18000), MNIST (M=70000) and REUTERS (M=267000). Witold Dzwinel, Rafał Wcisło 315 Automated Requirements Extraction for Scientific Software [abstract]Abstract: Requirements engineering is crucial for software projects, but formal requirements engineering is often ignored in scientific software projects. Scientists do not often see the benefit of directing their time and effort towards documenting requirements. Additionally, there is a lack of requirements engineering knowledge amongst scientists who develop software. We aim at helping scientists to easily recover and reuse requirements without acquiring prior requirements engineering knowledge. We apply an automated approach to extract requirements for scientific software from available knowledge sources, such as user manuals and project reports. The approach employs natural language processing techniques to match defined patterns in input text. We have evaluated the approach in three different scientific domains, namely seismology, building performance and computational fluid dynamics. The evaluation results show that 78--97% of the extracted requirement candidates are correctly extracted as early requirements. Yang Li, Emitzá Guzmán Ortega, Konstantina Tsiamoura, Florian Schneider, Bernd Bruegge

### ICCS 2015 Main Track (MT) Session 15

#### Chair: Dirk De Vos

 387 Interactive 180º Rear Projection Public Relations [abstract]Abstract: In the globalized world, good products may not be enough to reach potential clients if creative marketing strategies are not well delineated. Public relations are also important when it comes to capture clients attention, making the first contact between them and companies products while being persuasive enough to gain the of the client that the company has the right products to fit their needs. A virtual public relations is purposed, combining technology and a human like public relations capable of interacting with potential clients placed 180 degrees in front of the installation, by using gestures and sound. Four 4 Microsoft Kinects were used to develop de 180 degrees model for interaction, which allows recognition of gestures, sound sources, words, extract the face and body of the user and track users positions (including an heat map). Ricardo Alves, Aldric Négrier, Luís Sousa, J.M.F Rodrigues, Paulo Felizberto, Miguel Gomes, Paulo Bica 11 Identification of DNA Motif with Mutation [abstract]Abstract: The conventional way of identifying possible motif sequences in a DNA strand is to use representative scalar weight matrix for searching good match substring alignments. However, this approach, solely based on match alignment information, is susceptible to a high number of ambiguous sites or false positives if the motif sequences are not well conserved. A significant amount of time is then required to verify these sites for the suggested motifs. Hence in this paper, the use of mismatch alignment information in addition to match alignment information for DNA motif searching is proposed. The objective is to reduce the number of ambiguous false positives encountered in the DNA motif searching, thereby making the process more efficient for biologists to use. Jian-Jun Shu 231 A software tool for the automatic quantification of the left ventricle myocardium hyper-trabeculation degree [abstract]Abstract: Isolated left ventricular non-compaction (LVNC) is a myocardial disorder characterised by prominent ventricular trabeculations and deep recesses extending from the LV cavity to the subendocardial surface of the LV. Up to now, there is no common and stable solution in the medical community for quantifying and valuing the non-compacted cardiomyopathy. A software tool for the automatic quantification of the exact hyper-trabeculation degree in the left ventricle myocardium is designed, developed and tested. This tool is based on medical experience, but the possibility of the human appreciation error has been eliminated. The input data for this software are the cardiac images of the patients obtained by means of magnetic resonance. The output results are the percentage quantification of the trabecular zone with respect to the compacted area. This output is compared with human processing performed by medical specialists. The software proves to be a valuable tool to help diagnosis, so saving valuable diagnosis time. Gregorio Bernabe, Javier Cuenca, Pedro E. López de Teruel, Domingo Gimenez, Josefa González-Carrillo 453 Blending Sentence Optimization Weights of Unsupervised Approaches for Extractive Speech Summarization [abstract]Abstract: This paper evaluates the performance of two unsupervised approaches, Maximum Marginal Relevance (MMR) and concept-based global optimization framework for speech summarization. Automatic summarization is very useful techniques that can help the users browse a large amount of data. This study focuses on automatic extractive summarization on multi-dialogue speech corpus. We propose improved methods by blending each unsupervised approach at sentence level. Sentence level information is leveraged to improve the linguistic quality of selected summaries. First, these scores are used to filter sentences for concept extraction and concept weight computation. Second, we pre-select a subset of candidate summary sentences according to their sentence weights. Last, we extend the optimization function to a joint optimization of concept and sentence weights to cover both important concepts and sentences. Our experimental results show that these methods can improve the system performance comparing to the concept-based optimization baseline for both human transcripts and ASR output. The best scores are achieved by combining all three approaches, which are significantly better than the baseline system. Noraini Seman, Nursuriati Jamil 513 The CardioRisk Project: Improvement of Cardiovascular Risk Assessment [abstract]Abstract: The CardioRisk project addresses the coronary artery disease (CAD), namely, the management of myocardial infarction (MI) patients. The main goal is the development of personalized clinical models for cardiovascular (CV) risk assessment of acute events (e.g. death and new hospitalization), in order to stratify patients according to their care needs. This paper presents an overview of the scientific and technological issues that are under research and development. Three major scientific challenges can be identified: i) the development of fusion approaches to merge CV risk assessment tools; ii) strategies for the grouping (clustering) of patients; iii) biosignal processing techniques to achieve personalized diagnosis. At the end of the project, a set of algorithms/models must properly address these three challenges. Additionally, a clinical platform was implemented, integrating the developed models and algorithms. This platform supports a clinical observational study (100 patients) that is being carried out in Leiria Hospital Centre to validate the developed approach. Inputs from the hospital information system (demographics, biomarkers, clinical exams) are considered as well as an ECG signal acquired based on a Holter device. A real patient dataset provided by Santa Cruz Hospital, Portugal, comprising N=460 ACS-NSTEMI patients is also applied to perform initial validations (individual algorithms). The CardioRisk team is composed by two research institutions, the University of Coimbra (Portugal), Politecnico di Milano (Italy) and Leiria Hospital Centre (a Portuguese public hospital). Simão Paredes, Teresa Rocha, Paulo de Carvalho, Jorge Henriques, Diana Mendes, Ricardo Cabete, Ramona Cabiddu, Anna Maria Bianchi and João Morais

### ICCS 2015 Main Track (MT) Session 17

#### Chair: Ilya Valuev

 59 Swarming collapse under limited information flow between individuals [abstract]Abstract: Information exchange is critical to the execution and effectiveness of natural and artificial collective behaviors: fish schooling, birds flocking, amoebae aggregating or robots swarming. In particular, the emergence of dynamic collective responses in swarms confronted to complex environments underscore the central role played by social transmission of information. Here, the different possible origins of information flow bottlenecks are identified, and the associated effects on dynamic collective behaviors revealed using a combination of network-, control- and information-theoretic elements applied to a group of interacting self-propelled particles (SPPs). Specifically, we consider a minimalistic agent-based model consisting of N topologically interacting SPPs moving at constant speed through a domain having periodic boundaries. Each individual agent is characterized by its direction of travel and a canonical swarming behavior of the consensus type is examined. To account for the finiteness of the bandwidth, we consider synchronous information exchanges occurring every T = 1/2B, where the unit interval T is the minimum time interval between condition changes of data transmission signal. The agents move synchronously at discrete time steps T by a fixed distance upon receiving informational signals from their neighbors as per a linear update rule involving. We find a sufficient condition on the agents’ bandwidth B that guarantees the effectiveness of swarming while also highlighting the profound connection with the topology of the underlying interaction network. We also show that when decreasing B, the swarming behavior invariably vanishes following a second-order phase transition irrespectively of the intrinsic noise level. Roland Bouffanais 63 Multiscale simulation of organic electronics via massive nesting of density functional theory computational kernels [abstract]Abstract: Modelling is essential for development of organic electronics, such as organic light emitting diodes (OLEDs), organic field-effect transistors (OFETs) and organic photovoltaics (OPV). OLEDs have currently most applications, as they are already used in super-thin energy-efficient displays for television sets and smartphones, and in future will be used for lighting applications exploiting a world market worth tens of billions Euro. OLEDs should be further developed to increase their performance and durability, and reduce the currently high production costs. The conventional development process is very costly and time-demanding due to the large number of possible materials which have to be synthesized for the production and characterization of prototypes. Deeper understanding of the relationship between OLED device properties and materials structure allows for high-throughput materials screening and thus a tremendous reduction of development costs. In simulations, the properties of various materials one can be virtually and cost-effectively explored and compared to measurements. Based on these results, material composition, morphology and manufacturing processes can be systematically optimized. A typical OLED consists of a stack of multiple crystalline or amorphous organic layers. To compute electronic transport properties, e.g. charge mobilities, a quantum mechanical model, in particular the density functional theory (DFT) is commonly employed. Recently, we performed simulations of electronic processes in OLED materials achieved by multiscale modelling, i.e. by integrating sub-models on different length scales to investigate charge transport in thin films based on the experimentally characterized semi-conducting small molecules [1]. Here, we present a novel scale-out computational strategy to for a tightly coupled multiscale model consisting of a core region with 500 molecules (5000 pairs) of charge hopping sites and a embedding region, containing about 10000 electrostatically interacting molecules. The energy levels of each site depend on the local electrostatic environment yielding a significant contribution to the energy disor-der. This effect is explicitly taken into account in the quantum mechanical sub-model in a self-consistent manner, which represents however, a considerable computational challenge. Thus the total number of DFT calculations needed is of the order of 10^5-10^6. DFT models scale mostly as N^3, where N is the number of basis functions which is strongly related to the number of electrons. While DFT is implemented in a number of efficiently parallelized electronic structure codes, the computational scaling of a single DFT calculation applied for amorphous organic materials is naturally limited by the molecule size. After every iteration cycle, data are exchanged between all contained molecules of the self-consistence loop to update the electrostatic environment of each site. This requires that the DFT sub-model is executed employing a second-level parallelisation with a special scheduling strategy. The realisation of this model on high performance computer (HPC) systems has several issues: i) The DFT sub-models, which are stand-alone applications (such as NWChem or TURBOMOLE), have to be spawned at run time via process forking; ii) Large amounts of input and output data have to be transferred to and from the DFT sub-models though the cluster file system. These two requirements limit the computational performance and often conflict with the usage policies of common HPC environments. In addition, sub-model scheduling and DFT data pre-/post-processing have severe impact on the overall performance. To this end, we designed a DFT application programming interface (API) with different language bindings, such as Python and C++, allowing linking of DFT sub-models, independent of the concrete DFT implementation, to multiscale models. In addition, we propose solutions for in-core handling large input and output data as well as efficient scheduling algorithms. In this contribution, we will describe the architecture and outline the technical implementation of a framework for nesting DFT sub-models. We will demonstrate the use and analyse the performance of the framework for multiscale modelling of OLED materials. The framework provides an API which can be used to integrate DFT sub-models in other applications. [1] P. Friederich, F. Symalla, V. Meded, T. Neumann and W. Wenzel, “Ab Initio Treatment of Disorder Effects in Amorphous Organic Materials: Toward Parameter Free Materials Simulation”, Journal of Chemical Theory and Computation 10, 3720–3725 (2014). Angela Poschlad, Pascal Friederich, Timo Strunk, Wolfgang Wenzel and Ivan Kondov 189 Optimization and Practical Use of Composition Based Approaches Towards Identification and Collection of Genomic Islands and Their Ontology in Prokaryotes [abstract]Abstract: Motivation: Horizontally transferred genomic islands (islands, GIs) have been referred to as important factors which contribute towards the emergences of pathogens and outbreak instances. The development of tools towards the identification of such elements and retracing their distribution patterns will help to understand how such cases arise. Sequence composition has been used to identify islands, infer their phylogeny; and determine their relative times of insertions. The collection and curation of known islands will enhance insight into island ontology and flow. Results: This paper introduces the merger of SeqWord Genomic Islands Sniffer (SWGIS) which utilizes composition based approaches for identification of islands in bacterial genomic sequences and the Predicted Genomic Islands (Pre_GI) database which houses 26,744 islands found in 2,407 bacterial plasmids and chromosomes. SWGIS is a standalone program that detects genomic islands using a set of optimized parametric measures with estimates of acceptable false positive and false negative rates. Pre_GI is novel repository that includes island ontology and flux. This study furthermore illustrates the need for parametric optimization towards the prediction of islands to minimize false negative and false positive predictions. In addition Pre_GI emphasizes the practicality of compounded knowledge a database affords in the detection and visualization of ontological links between islands. Availability: SWGIS is freely available on the web at http://www.bi.up.ac.za/SeqWord/sniffer/index.html. Pre_GI is freely accessible at http://pregi.bi.up.ac.za/index.php. Rian Pierneef, Oliver Bezuidt, Oleg Reva