13 Zentrale Universitätseinrichtungen

Permanent URI for this collectionhttps://elib.uni-stuttgart.de/handle/11682/14

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Open Access
Process migration in a parallel environment
(Stuttgart : Höchstleistungsrechenzentrum, Universität Stuttgart, 2016) Reber, Adrian; Resch, Michael (Prof. Dr.- Ing. Dr. h.c. Dr. h.c. Prof. E.h.)
To satisfy the ever increasing demand for computational resources, high performance computing systems are becoming larger and larger. Unfortunately, the tools supporting system management tasks are only slowly adapting to the increase in components in computational clusters. Virtualization provides concepts which make system management tasks easier to implement by providing more flexibility for system administrators. With the help of virtual machine migration, the point in time for certain system management tasks like hardware or software upgrades no longer depends on the usage of the physical hardware. The flexibility to migrate a running virtual machine without significant interruption to the provided service makes it possible to perform system management tasks at the optimal point in time. In most high performance computing systems, however, virtualization is still not implemented. The reason for avoiding virtualization in high performance computing is that there is still an overhead accessing the CPU and I/O devices. This overhead continually decreases and there are different kind of virtualization techniques like para-virtualization and container-based virtualization which minimize this overhead further. With the CPU being one of the primary resources in high performance computing, this work proposes to migrate processes instead of virtual machines thus avoiding any overhead. Process migration can either be seen as an extension to pre-emptive multitasking over system boundaries or as a special form of checkpointing and restarting. In the scope of this work process migration is based on checkpointing and restarting as it is already an established technique in the field of fault tolerance. From the existing checkpointing and restarting implementations, the best suited implementation for process migration purposes was selected. One of the important requirements of the checkpointing and restarting implementation is transparency. Providing transparent process migration is important enable the migration of any process without prerequisites like re-compilation or running in a specially prepared environment. With process migration based on checkpointing and restarting, the next step towards providing process migration in a high performance computing environment is to support the migration of parallel processes. Using MPI is a common method of parallelizing applications and therefore process migration has to be integrated with an MPI implementation. The previously selected checkpointing and restarting implementation was integrated in an MPI implementation, and thus enabling the migration of parallel processes. With the help of different test cases the implemented process migration was analyzed, especially in regards to the time required to migrated a process and the advantages of optimizations to reduce the process’ downtime during migration.
Open Access
3D visualization of multivariate data
(2012) Sanftmann, Harald; Weiskopf, Daniel (Prof. Dr.)
Nowadays large amounts of data are organized in tables, especially in relational databases where the rows store the data items to which multiple attributes are stored in the columns. Information stored this way, having multiple (more than two or three) attributes, can be treated as multivariate data. Therefore, visualization methods for multivariate data have a large application area and high potential utility. This thesis focuses on the application of 3D scatter plots for the visualization of multivariate data. When dealing with 3D, spatial perception needs to be exploited, by effectively using depth cues to convey spatial information to the user. To improve the presentation of individual 3D scatter plots, a technique is presented that applies illumination to them, thus using the shape-from-shading depth cue. To enable the analysis not only of 3D but of multivariate data, a novel technique is introduced that allows the navigation between 3D scatter plots. Inspecting the large number of 3D scatter plots that can be projected from a multivariate data set is very time consuming. The analysis of multivariate data can benefit from automatic machine learning approaches. A presented method uses decision trees to increase the speed a user can gain an understanding of the multivariate data at no extra cost. Stereopsis can also support the display of 3D scatter plots. Here an improved anaglyph rendering technique is presented, significantly reducing ghosting artifacts. The technique is not only applicable for information visualization, but for general rendering or to present stereoscopic image data. Some information visualization algorithms require high computation time. Many of these algorithms can be parallelized to run interactively. A framework that supports the parallelization on shared and distributed memory systems is presented.
Open Access
Visualization and mesoscopic simulation in systems biology
(2013) Falk, Martin Samuel; Ertl, Thomas (Prof. Dr.)
A better understanding of the internal mechanisms and interplays within a single cell is key to the understanding of life. The focus of this thesis lies on the mechanism of cellular signal transduction, i.e. relaying a signal from outside the cell by different means of transport toward its target inside the cell. Besides experiments, understanding can also be achieved by numerical simulations of cellular behavior which require theoretical models to be designed and evaluated. This is where systems biology closely relates and depends on recent research results in computer science in order to deal with the modeling, the simulation, and the analysis of the computational results. Since a single cell can consist of billions of atoms, the simulation of intracellular processes requires a simplified, mesoscopic model. The simulation domain has to be three dimensional to consider the spatial, possibly asymmetric, intracellular architecture filled with individual particles representing signaling molecules. In contrast to continuous models defined by systems of partial differential equations, a particle-based model allows tracking individual molecules moving through the cell. The overall process of signal propagation usually requires between minutes and hours to complete, but the movement of molecules and the interactions between them have to be determined in the microsecond range. Hence, the computation of thousands of consecutive time steps is necessary, requiring several hours or even days of computational time for a non-parallel simulation. To speed up the simulation, the parallel hardware of current central processing units (CPUs) and graphics processing units (GPUs) can be employed. Finally, the resulting data has to be analyzed by domain experts and, therefore, has to be represented in meaningful ways. Typical prevalent analysis methods include the aggregation of the data in tables or simple 2D graph plots, sometimes 3D plots for continuous data. Despite the fact that techniques for interactive visualization of data in 3D are well-known, so far none of the methods have been applied to the biological context of single cell models and specialized visualizations fitted to the experts’ need are missing. Another issue is the hardware available to the domain experts that can be used for the task of visualizing the increasing amount of time-dependent data resulting from simulations. It is important that the visualization keeps up with the simulations to ensure that domain experts can still analyze their data sets. To deal with the massive amount of data to come, compute clusters will be necessary with specialized hardware dedicated to data visualization. It is, thus, important, to develop visualization algorithms for this dedicated hardware, which is currently available as GPU. In this thesis, the computational power of recent many-core architectures (CPUs and GPUs) is harnessed for both the simulation and the visualizations. Novel parallel algorithms are introduced to parallelize the spatio-temporal, mesoscopic particle simulation to fit the architectures of CPU and GPU in a similar way. Besides molecular diffusion, the simulation considers extracellular effects on the signal propagation as well as the import of molecules into the nucleus and a dynamic cytoskeleton. An extensive comparison between different configurations is performed leading to the conclusion that the usage of GPUs is not always beneficial. For the visual data analysis, novel interactive visualization techniques were developed to visualize the 3D simulation results. Existing glyph-based approaches are combined in a new way facilitating the visualization of the individual molecules in the interior of the cell as well as their trajectories. A novel implementation of the depth of field effect combined with additional depth cues and coloring aid the visual perception and reduce visual clutter. To obtain a continuous signal distribution from the discrete particles, techniques known from volume rendering are employed. The visualization of the underlying atomic structures provides new detailed insights and can be used for educational purposes besides showing the original data. A microscope-like visualization allows for the first time to generate images of synthetic data similar to images obtained in wet lab experiments. The simulation and the visualizations are merged into a prototypical framework, thereby supporting the domain expert during the different stages of model development, i.e. design, parallel simulation, and analysis. Although the proposed methods for both simulation and visualization were developed with the study of single-cell signal transduction processes in mind, they are also applicable to models consisting of several cells and other particle-based scenarios. Examples in this thesis include the diffusion of drugs into a tumor, the detection of protein cavities, and molecular dynamics data from laser ablation simulations, among others.
Open Access
Increased flexibility and dynamics in distributed applications and processes through resource decoupling
(2014) Kipp, Alexander; Resch, Michael (Prof. Dr.-Ing.)
Continuously increasing complexity of products and services requires more and more specialised expertise as well as relevant support by specialised IT tools and services. However, these services require expert knowledge as well, particularly in order to apply and use these services and tools in an efficient and optimal way. To this end, this thesis introduces a new virtualisation approach, allowing for both, the transparent integration of services in abstract process description languages, as well as the role based integration of human experts in this processes. The developed concept of this thesis has been realised by: - Enhancing the concept of web services with a service virtualisation layer, allowing for the transparent usage, adaptation and orchestration of services - Enhancing the developed concept towards a “Dynamic Session Management” environment, enabling the transparent and role-based integration of human experts following the SOA paradigm - Developing a collaboration schema, allowing for setting up and steering synchronous collaboration sessions between human experts. This enhancement also considers the respective user context and provides the best suitable IT based tooling support. The developed concept has been applied to scientific and economic application fields with a respective reference realisation.
Open Access
Advanced visualization techniques for flow simulations : from higher-order polynomial data to time-dependent topology
(2013) Üffinger, Markus; Ertl, Thomas (Prof. Dr.)
Computational Wuid dynamics (CFD) has become an important tool for predicting Fluid behavior in research and industry. Today, in the era of tera- and petascale computing, the complexity and the size of simulations have reached a state where an extremely large amount of data is generated that has to be stored and analyzed. An indispensable instrument for such analysis is provided by computational Wow visualization. It helps in gaining insight and understanding of the Wow and its underlying physics, which are subject to a complex spectrum of characteristic behavior, ranging from laminar to turbulent or even chaotic characteristics, all of these taking place on a wide range of length and time scales. The simulation side tries to address and control this vast complexity by developing new sophisticated models and adaptive discretization schemes, resulting in new types of data. Examples of such emerging simulations are generalized Vnite element methods or hp-adaptive discontinuous Galerkin schemes of high-order. This work addresses the direct visualization of the resulting higher-order Veld data, avoiding the traditional resampling approach to enable a more accurate visual analysis. The second major contribution of this thesis deals with the inherent complexity of Wuid dynamics. New feature-based and topology-based visualization algorithms for unsteady Wow are proposed to reduce the vast amounts of raw data to their essential structure. For the direct visualization pixel-accurate techniques are presented for 2D Veld data from generalized Vnite element simulations, which consist of a piecewise polynomial part of high order enriched with problem-dependent ansatz functions. Secondly, a direct volume rendering system for hp-adaptive Vnite elements, which combine an adaptive grid discretization with piecewise polynomial higher-order approximations, is presented. The parallel GPU implementation runs on single workstations, as well as on clusters, enabling a real-time generation of high quality images, and interactive exploration of the volumetric polynomial solution. Methods for visual debugging of these complex simulations are also important and presented. Direct Wow visualization is complemented by new feature and topology-based methods. A promising approach for analyzing the structure of time-dependent vector Velds is provided by Vnite-time Lyapunov exponent (FTLE) Velds. In this work, interactive methods are presented that help in understanding the cause of FTLE structures, and novel approaches to FTLE computation are developed to account for the linearization error made by traditional methods. Building on this, it is investigated under which circumstances FTLE ridges represent Lagrangian coherent structures (LCS)—the timedependent counterpart to separatrices of traditional “steady” vector Veld topology. As a major result, a novel time-dependent 3D vector Veld topology concept based on streak surfaces is proposed. Streak LCS oUer a higher quality than corresponding FTLE ridges, and animations of streak LCS can be computed at comparably low cost, alleviating the topological analysis of complex time-dependent Velds.
Open Access
Visualization techniques for parallel coordinates
(2013) Heinrich, Julian; Weiskopf, Daniel (Prof. Dr.)
Visualization plays a key role in knowledge discovery, visual data exploration, and visual analytics. Static images are an effective tool for visual communication, summarization, and pattern extraction in large and complex datasets. Only together with human-computer-interaction techniques, visual interfaces enable an analyst to explore large information spaces and to drive the whole analytical reasoning process. Scatterplots and parallel coordinates are well-recognized visualization techniques that are commonly employed for statistics (both explorative and descriptive) and data-mining, but are also gaining importance for scientific visualization. While scatterplots are restricted to the display of at most three dimensions due to the orthogonal layout of coordinate axes, a parallel arrangement allows for the visualization of multiple attributes of a dataset. Although both techniques rely on projections of higher-dimensional geometry and are related by a point–line duality, parallel coordinates enjoy great popularity for the visualization and analysis of multivariate data. Despite their popularity, parallel coordinates are subject to a number of limitations that remain to be solved. For large datasets, the potentially high amount of overlapping lines may hinder the observer from visually extracting meaningful patterns. Encoding observations with polylines make it difficult to follow lines over all dimensions, as they lose visual continuation across the axes. Clusters cannot be represented by the geometry of lines, and the order of axes has a high impact on the patterns exhibited by parallel coordinates. This thesis presents visualization techniques for parallel coordinates that address these limitations. As a foundation, an extensive review of the state of the art of parallel coordinates will be given. Based on the point–line duality, the existing model of continuous scatterplots is adapted to parallel coordinates for the visualization of data defined on continuous domains. To speed up computation and obtain interactive frame rates, a scalable and progressive rendering algorithm is introduced that further allows for arbitrary reconstruction and interpolation schemes. A curve-bundling model for parallel coordinates is evaluated with a user study showing that bundling is effective for cluster visualization based on geometric cues while being equally capable of revealing correlations between neighboring axes. To address the axis-order problem, a graph-based approach is presented that allows for the visualization of all pairwise relations in a matrix layout without redundancy. Finally, the use of parallel coordinates is demonstrated for real datasets from computational fluid dynamics, motion capturing, bioinformatics, and systems biology.
Open Access
Service level agreements for job submission and scheduling in high performance computing
(2014) Kübert, Roland; Resch, Michael (Prof. Dr.-Ing.)
This thesis introduces the concept of long-term service level agreements for the offering of quality of service in high performance computing. Feasiblity of the approach is demonstrated by a proof of concept implementation. A simulation tool developed in the scope of this thesis is subsequently used to investigate sensible parameters for quality of service classes in the high performance computing domain.
Open Access
Enhanced SLA management in the high performance computing domain
(2011) Koller, Bastian; Resch, Michael (Prof. Dr.-Ing. Dr. h.c.)
This thesis describes a Service Level Agreement Schema for the High Performance Computing domain and the according architecture to allow for SLA Management, which are both developed on base of three different use cases.
Open Access
Die geregelte logische Uhr, eine globale Uhr für die tracebasierte Überwachung paralleler Anwendungen
(2000) Rabenseifner, Rolf; Rothermel, Kurt (Prof. Dr.)
Das Aufzeichnen und Darstellen des Programmflusses sowie des Nachrichtenaustauschs paralleler Anwendungen ist schwierig, wenn jeder Prozessor eine eigene Uhr besitzt, und diese Uhren nicht synchronisiert sind. Mehrere Strategien zur Bildung einer globalen Uhrzeit werden in einem Überblick dargestellt, und die Grenzen werden aufgezeigt. Die geregelte logische Uhr, eine neue Methode auf der Basis von Lamports logischer Uhr, wird vorgestellt. Ungenaue Zeitstempel aus Tracefiles werden derart modifiziert, daß sie die Uhrenbedingung erfüllen, d.h. daß der Empfang einer Nachricht einen späteren Zeitstempel als das zugehörige Sendeereignis besitzt. Mit dem Regler wird das Maximum aller lokalen Prozessoruhren als Basis für eine globale Zeit angenähert. Die korrigierten Zeitstempel ermöglichen Leistungsmessungen, bei denen die Ereignisse in verschiedenen Prozessen liegen. Eine stückweise lineare rückwärtige Amortisation der Uhrenkorrekturen garantiert, daß die Fehler bei Messungen von Zeitintervallen zwischen Ereignissen im selben Prozeß minimal sind. Bei der Erstellung eines Tracefiles ist kein zusätzlicher Protokollaufwand nötig. Die geregelte logische Uhr kann als Filter für Tracefiles implementiert werden. Sie kann aber auch in Monitor- und Debuggingwerkzeuge integriert werden.
Open Access
Visualization techniques for group structures in graphs
(2015) Vehlow, Corinna; Weiskopf, Daniel (Prof. Dr.)
Graph visualization plays a key role analyzing relations between objects. With increasing size of the graph, it becomes difficult to understand global and local structures of the graph. Grouping objects of the graph based on their attributes or relations helps reveal global structures. Visualizing these group structures together with the graph topology can highlight central objects and reveal outliers. The ability of a visualization to help detecting these features becomes more difficult for groups that overlap or change over time. In many applications, groups cannot be interpreted as disjoint sets of objects. In fact, objects are often involved in several groups, sometimes even to different extent. With the existing types of overlapping groups, further analysis tasks arise that need to be considered for the visualization. In addition, real-world scenarios are not static but change over time and so do relations among objects. With the graph topology changing over time, the group structure changes as well. The challenge for visualizations of dynamic groups in dynamic graphs is to facilitate the analysis of group-related features not only for individual points in time but over time, showing group evolution events. This thesis presents visualization techniques for group structures in graphs that address these challenges: overlap and time dependency. As a basis, a survey of the state of the art in visualizing group structures in graphs is presented. The first part of this thesis is dedicated to the visualization of overlapping groups in static graphs, where different types of overlaps are considered. With each technique, the complexity of the groups increases. First, a visual analytics system for crisp overlapping groups in multivariate graphs is presented. This system integrates interactive filtering of large and dense networks with groupbased layouts of the resulting subnetworks and a technique to compare those subnetworks. Second, a technique that visualizes fuzzy overlapping groups in a graph based on layout strategies and further visual mappings is presented. This technique facilitates the investigation of fuzzy group memberships at different levels of detail based on a hierarchical aggregation model. In contrast to these techniques, the third visualization technique shows groups based on multivariate edge attributes rather than vertex attributes or the topology of the graph. In particular, edge-edge relations are visualized as curves that are directly integrated into the node-link diagram representing the object-relation structure. The second part is dedicated to visualization techniques for dynamic groups in dynamic graphs. Again, the complexity of the group structure rises from the first technique addressing flat groups to the second technique addressing more complex hierarchical groups. Within both techniques, the evolution of groups is encoded using a flow metaphor. The first technique visualizes the partially aggregated graphs by node-link diagrams, whereas the second technique is based on an extended adjacency matrix representation that encodes the hierarchical structure of vertices as well as changes in the graph topology. All presented techniques visualize the group structure integrated with the graph topology in a single image. Finally, the use of all techniques is demonstrated for real data sets from biology, one of the main application domains of group structures in graphs.

13 Zentrale Universitätseinrichtungen

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