05 Fakultät Informatik, Elektrotechnik und Informationstechnik
Permanent URI for this collectionhttps://elib.uni-stuttgart.de/handle/11682/6
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Item Open Access Visualization challenges in distributed heterogeneous computing environments(2015) Panagiotidis, Alexandros; Ertl, Thomas (Prof. Dr.)Large-scale computing environments are important for many aspects of modern life. They drive scientific research in biology and physics, facilitate industrial rapid prototyping, and provide information relevant to everyday life such as weather forecasts. Their computational power grows steadily to provide faster response times and to satisfy the demand for higher complexity in simulation models as well as more details and higher resolutions in visualizations. For some years now, the prevailing trend for these large systems is the utilization of additional processors, like graphics processing units. These heterogeneous systems, that employ more than one kind of processor, are becoming increasingly widespread since they provide many benefits, like higher performance or increased energy efficiency. At the same time, they are more challenging and complex to use because the various processing units differ in their architecture and programming model. This heterogeneity is often addressed by abstraction but existing approaches often entail restrictions or are not universally applicable. As these systems also grow in size and complexity, they become more prone to errors and failures. Therefore, developers and users become more interested in resilience besides traditional aspects, like performance and usability. While fault tolerance is well researched in general, it is mostly dismissed in distributed visualization or not adapted to its special requirements. Finally, analysis and tuning of these systems and their software is required to assess their status and to improve their performance. The available tools and methods to capture and evaluate the necessary information are often isolated from the context or not designed for interactive use cases. These problems are amplified in heterogeneous computing environments, since more data is available and required for the analysis. Additionally, real-time feedback is required in distributed visualization to correlate user interactions to performance characteristics and to decide on the validity and correctness of the data and its visualization. This thesis presents contributions to all of these aspects. Two approaches to abstraction are explored for general purpose computing on graphics processing units and visualization in heterogeneous computing environments. The first approach hides details of different processing units and allows using them in a unified manner. The second approach employs per-pixel linked lists as a generic framework for compositing and simplifying order-independent transparency for distributed visualization. Traditional methods for fault tolerance in high performance computing systems are discussed in the context of distributed visualization. On this basis, strategies for fault-tolerant distributed visualization are derived and organized in a taxonomy. Example implementations of these strategies, their trade-offs, and resulting implications are discussed. For analysis, local graph exploration and tuning of volume visualization are evaluated. Challenges in dense graphs like visual clutter, ambiguity, and inclusion of additional attributes are tackled in node-link diagrams using a lens metaphor as well as supplementary views. An exploratory approach for performance analysis and tuning of parallel volume visualization on a large, high-resolution display is evaluated. This thesis takes a broader look at the issues of distributed visualization on large displays and heterogeneous computing environments for the first time. While the presented approaches all solve individual challenges and are successfully employed in this context, their joint utility form a solid basis for future research in this young field. In its entirety, this thesis presents building blocks for robust distributed visualization on current and future heterogeneous visualization environments.Item Open Access Prediction and similarity models for visual analysis of spatiotemporal data(2022) Tkachev, Gleb; Ertl, Thomas (Prof. Dr.)Ever since the early days of computers, their usage have become essential in natural sciences. Whether through simulation, computer-aided observation or data processing, the progress in computer technology have been mirrored by the constant growth in the size of scientific data. Unfortunately, as the data sizes grow, and human capabilities remains constant, it becomes increasingly difficult to analyze and understand the data. Over the last decades, visualization experts have proposed many approaches to address the challenge, but even these methods have their limitations. Luckily, recent advances in the field of Machine Learning can provide the tools needed to overcome the obstacle. Machine learning models are a particularly good fit as they can both benefit from the large amount of data present in the scientific context and allow the visualization system to adapt to the problem at hand. This thesis presents research into how machine learning techniques can be adapted and extended to enable visualization of scientific data. It introduces a diverse set of techniques for analysis of spatiotemporal data, including detection of irregular behavior, self-supervised similarity metrics, automatic selection of visual representations and more. It also discusses the general challenges of applying Machine Learning to Scientific Visualization and how to address them.Item Open Access Uncertainty-aware visualization techniques(2021) Schulz, Christoph; Weiskopf, Daniel (Prof. Dr.)Nearly all information is uncertainty-afflicted. Whether and how we present this uncertainty can have a major impact on how our audience perceives such information. Still, uncertainty is rarely visualized and communicated. One difficulty is that we tend to interpret illustrations as truthful. For example, it is difficult to understand that a drawn point’s presence, absence, and location may not convey its full information. Similarly, it may be challenging to classify a point within a probability distribution. One must learn how to interpret uncertainty-afflicted information. Accordingly, this thesis addresses three research questions: How can we identify and reason about uncertainty? What are approaches to modeling flow of uncertainty through the visualization pipeline? Which methods are suitable for harnessing uncertainty? The first chapter is concerned with sources of uncertainty. Then, approaches to model uncertainty using descriptive statistics and unsupervised learning are discussed. Also, a model for validation and evaluation of visualization methods is proposed. Further, methods for visualizing uncertainty-afflicted networks, trees, point data, sequences, and time series are presented. The focus lies on modeling, propagation, and visualization of uncertainty. As encodings of uncertainty, we propose wave-like splines and sampling-based transparency. As an overarching approach to adapt existing visualization methods for uncertain information, we identify the layout process (the placement of objects). The main difficulty is that these objects are not simple points but distribution functions or convex hulls. We also develop two stippling-based methods for rendering that utilize the ability of the human visual system to cope with uncertainty. Finally, I provide insight into possible directions for future research.Item Open Access Interactive web-based visualization(2018) Mwalongo, FinianThe visualization of large amounts of data, which cannot be easily copied for processing on a user’s local machine, is not yet a fully solved problem. Remote visualization represents one possible solution approach to the problem, and has long been an important research topic. Depending on the device used, modern hardware, such as high-performance GPUs, is sometimes not available. This is another reason for the use of remote visualization. Additionally, due to the growing global networking and collaboration among research groups, collaborative remote visualization solutions are becoming more important. The additional use of collaborative visualization solutions is eventually due to the growing global networking and collaboration among research groups. The attractiveness of web-based remote visualization is greatly increased by the wide availability of web browsers on almost all devices; these are available today on all systems - from desktop computers to smartphones. In order to ensure interactivity, network bandwidth and latency are the biggest challenges that web-based visualization algorithms have to solve. Despite the steady improvements in available bandwidth, these improvements are still significantly slower than, for example, processor performance, resulting in increasing the impact of this bottleneck. For example, visualization of large dynamic data in low-bandwidth environments can be challenging because it requires continuous data transfer. However, bandwidth improvement alone cannot improve the latency because it is also affected by factors such as the distance between server and client and network utilization. To overcome these challenges, a combination of techniques is needed to customize the individual processing steps of the visualization pipeline, from efficient data representation to hardware-accelerated rendering on the client side. This thesis first deals with related work in the field of remote visualization with a particular focus on interactive web-based visualization and then presents techniques for interactive visualization in the browser using modern web standards such as WebGL and HTML5. These techniques enable the visualization of dynamic molecular data sets with more than one million atoms at interactive frame rates using GPU-based ray casting. Due to the limitations which exist in a browser-based environment, the concrete implementation of the GPU-based ray casting had to be customized. Evaluation of the resulting performance shows that GPU-based techniques enable the interactive rendering of large data sets and achieve higher image quality compared to polygon-based techniques. In order to reduce data transfer times and network latency, and improve rendering speed, efficient approaches for data representation and transmission are used. Furthermore, this thesis introduces a GPU-based volume-ray marching technique based on WebGL 2.0, which uses progressive brick-wise data transfer, as well as multiple levels of detail in order to achieve interactive volume rendering of datasets stored on a server. The concepts and results presented in this thesis contribute to the further spread of interactive web-based visualization. The algorithmic and technological advances that have been achieved form a basis for further development of interactive browser-based visualization applications. At the same time, this approach has the potential for enabling future collaborative visualization in the cloud.Item Open Access Visualization of two-phase flow dynamics : techniques for droplet interactions, interfaces, and material transport(2017) Karch, Grzegorz Karol; Ertl, Thomas (Prof. Dr.)Computational visualization allows scientists and engineers to better understand simulation data and gain insights into the studied natural processes. Particularly in the field of computational fluid dynamics, interactive visual presentation is essential in the investigation of physical phenomena related to gases and liquids. To ensure effective analysis, flow visualization techniques must adapt to the advancements in the field of fluid dynamics that benefits substantially from the growing computational power of both commodity desktops and supercomputers on the one hand, and steadily expanding knowledge about fluid physics on the other. A prominent example of these advances can be found in the research of two-phase flow with liquid droplets and jets, where high performance computation and sophisticated algorithms for phase tracking enable well resolved and physically accurate simulations of liquid dynamics. Yet, the field of two-phase flow has remained largely unexplored in visualization research so far, leaving the scientists and engineers with a number of challenges when analyzing the data. These include the difficulty in tracking and investigating topological events in large droplet groups, high complexity of droplet dynamics due to the involved interfaces, and a limited choice of high quality interactive methods for the analysis of related transport phenomena. It is therefore the aim of this thesis to address these challenges by providing a multi-scale approach for the visual investigation of two-phase flow, with the focus on the analysis of droplet interaction, fluid interfaces, and material transport. To address the problem of analyzing highly complex two-phase flow simulations with droplet groups and jets, a linked-view approach with three-dimensional and abstract space-time graph representation of droplet dynamics is proposed. The interactive brushing and linking allows for general exploration of topological events as well as detailed inspection of dynamics in terms of oscillations and rotations of droplets. Another approach further examines the separation of liquid phases by segmenting liquid volumes according to their topological changes in future time. For visualization, boundary surfaces of these volume segments are extracted that reveal intricate details of droplet topology dynamics. Additionally, within this framework, visualization of advected particles corresponding to arbitrarily selected segment provides useful insights into the spatio-temporal evolution of the segment. The analysis of interfaces is necessary to understand the interplay of interface dynamics and the dynamics of droplet interactions. A commonly used technique for interface tracking in the volume of fluid-based simulations is the piecewise linear approximation which, although accurate, can affect the quality of the simulation results. To study the influence of the interface reconstruction on the phase tracking procedure, a visualization method is presented that extracts the interfaces by means of the first-order Taylor approximation, and provides several derived quantities that help assess the simulation results in relation to the interface reconstruction quality. The liquid interface is further investigated from the physical standpoint with an approach based on quantities derived from velocity and surface tension gradients. The developed method supports examination of surface tension forces and their impact on the interface instability, as well as detailed analysis of interface deformation characteristics. A line of research important for engineering applications is the analysis of electric fields on droplet interfaces. It is, however, complicated by higher-order elements used in the simulations to preserve field discontinuities. A visualization method has been developed that correctly visualizes these discontinuities at material boundaries. Additionally, the employed space-time representation of the droplet-insulator contact line reveals characteristics of electric field dynamics. The dynamics of droplets are often examined assuming single-phase flow, for instance when the internal material transport is of interest. From the visualization perspective, this allows for adaption of traditional vector field visualization techniques to the investigation of the studied phenomena. As one such concept, dye based visualization is proposed that extends the transport analysis to advection-diffusion problems, therefore revealing true transport behavior. The employed high quality advection preserves fine details of the dye, while the implementation on graphics processing units ensures interactive visualization. Several streamline-based concepts are applied in space-time representation of 2D unsteady flow. By interpreting time as the third spatial dimension, many 3D streamline-based visualization techniques can be applied to investigate 2D unsteady flow. The introduced vortex core ribbons support the examination of vortical flow behavior by revealing rotation near the core lines. For the study of topological structures, a method has been developed that extracts separatrices implicitly as boundaries of regions with different flow behavior, and therefore avoids potentially complicated explicit extraction of various topological structures. All proposed techniques constitute a novel multi-scale approach for visual analysis of two-phase flow. The analysis of droplet interactions is addressed with visualization of the phenomena leading to breakups and with detailed visual inspection of these breakups. On the interface level, techniques for the interface analysis give insights into the simulation quality, mechanisms behind topology changes, as well as the behavior of electrically charged droplets. Further down the scale, the dye-based visualization, streamline-based concepts for space-time analysis, and the implicit extraction of flow topology allow for the investigation of droplet internal transport as well as general single-phase flow scenarios. The applicability of the proposed methods extends, in a varying degree, beyond the use in two-phase flow. Their usability is demonstrated on data from simulations based on Navier-Stokes equations that exemplify practical problems in the research of fluid dynamics.Item Open Access Impact of gaze uncertainty on AOIs in information visualisations(2022) Wang, Yao; Koch, Maurice; Bâce, Mihai; Weiskopf, Daniel; Bulling, AndreasGaze-based analysis of areas of interest (AOIs) is widely used in information visualisation research to understand how people explore visualisations or assess the quality of visualisations concerning key characteristics such as memorability. However, nearby AOIs in visualisations amplify the uncertainty caused by the gaze estimation error, which strongly influences the mapping between gaze samples or fixations and different AOIs. We contribute a novel investigation into gaze uncertainty and quantify its impact on AOI-based analysis on visualisations using two novel metrics: the Flipping Candidate Rate (FCR) and Hit Any AOI Rate (HAAR). Our analysis of 40 real-world visualisations, including human gaze and AOI annotations, shows that gaze uncertainty frequently and significantly impacts the analysis conducted in AOI-based studies. Moreover, we analysed four visualisation types and found that bar and scatter plots are usually designed in a way that causes more uncertainty than line and pie plots in gaze-based analysis.Item Open Access Vision-based methods for evaluating visualizations(2018) Netzel, Rudolf; Weiskopf, Daniel (Prof. Dr.)Item Open Access Animated surfaces in physically-based simulation(2018) Huber, Markus; Weiskopf, Daniel (Prof. Dr.)Physics-based animation has become a ubiquitous element in all application areas of computer animation, especially in the entertainment sector. Animation and feature films, video games, and advertisement contain visual effects using physically-based simulation that blend in seamlessly with animated or live-action productions. When simulating deformable materials and fluids, especially liquids, objects are usually represented by animated surfaces. The visual quality of these surfaces not only depends on the actual properties of the surface itself but also on its generation and relation to the underlying simulation. This thesis focuses on surfaces of cloth simulations and fluid simulations based on Smoothed Particle Hydrodynamics (SPH), and contributes to improving the creation of animations by specifying surface shapes, modeling contact of surfaces, and evaluating surface effects of fluids. In many applications, there is a reference given for a surface animation in terms of its shape. Matching a given reference with a simulation is a challenging task and similarity is often determined by visual inspection. The first part of this thesis presents a signature for cloth animations that captures characteristic shapes and their temporal evolution. It combines geometric features with physical properties to represent accurately the typical deformation behavior. The signature enables calculating similarities between animations and is applied to retrieve cloth animations from collections by example. Interactions between particle-based fluids and deformable objects are usually modeled by sampling the deformable objects with particles. When interacting with cloth, however, this would require resampling the surface at large planar deformations and the thickness of cloth would be bound to the particle size. This problem is addressed in this thesis by presenting a two-way coupling technique for cloth and fluids based on the simulation mesh of the textile. It allows robust contact handling and intuitive control of boundary conditions. Further, a solution for intersection-free fluid surface reconstruction at contact with thin flexible objects is presented. The visual quality of particle-based fluid animation highly depends on the properties of the reconstructed surface. An important aspect of the reconstruction method is that it accurately represents the underlying simulation. This thesis presents an evaluation of surfaces at interfaces of SPH simulations incorporating the connection to the simulation model. A typical approach in computer graphics is compared to surface reconstruction used in material sciences. The behavior of free surfaces in fluid animations is highly influenced by surface tension. This thesis presents an evaluation of three types of surface tension models in combination with different pressure force models for SPH to identify the individual characteristics of these models. Systematic tests using a set of benchmark scenes are performed to reveal strengths and weaknesses, and possible areas of applications.Item Open Access Interactive visual analysis of biomolecular simulations(2015) Krone, Michael; Ertl, Thomas (Prof. Dr.)Molecular dynamics simulations can give detailed insights into the properties of biomolecules on an atomistic level. Improvements in the domain of simulation codes as well as of the available hardware enable the simulation of invariably more complex molecular processes. Molecular simulation is therefore often described as a “computational microscope” that makes it possible to run experiments virtually and thus gain insights into the function of proteins and other biomolecules. Although molecular dynamics simulations have inherent restrictions, the results can partially be obtained more reproducible, reliable, and safely than using wet lab experiments. The scope of application ranges from fundamental questions like the formation of protein conformations or the effect of mutations to complex analyses like synthesis rates of biodiesel in biotechnology or drug binding in medicine. Visualization of the simulation results is an essential part of the interpretation of these virtual experiments. It is so to say the ocular of the computational microscope, which makes the data visible. Interactive visualization facilitates making discoveries, since it fosters an exploratory visual analysis of the data. Molecular models tailored to specific problems illustrate the particular properties of the visualized biomolecules. Examples are abstract representations that show the functional structure of a protein, or molecular surfaces that depict the contact surface between a molecule and a solvent. Available visualization techniques are, however, often not efficient enough to ensure an interactive exploration of large, dynamic data. A more comprehensive analysis that goes beyond this direct visualization of the simulation data is attained through feature extractions, which are executed as part of the visualization. Here, derived features of the simulated biomolecules like potential binding sites for reactants are extracted from the raw data, that is, the positions and elements of the atoms. Similar to the existing visualization techniques, previous analysis methods are in most cases not applicable in real-time and, thus, restricted to static data like single time steps of a simulation. For simulation data, however, processes that extend over a period of time can be of particular interest, for example conformational changes of a protein. Since the available feature extraction methods are not applicable in real-time, the results have to be precomputed for all time steps. Parameter changes imply a costly recalculation for the whole simulation. Hence, an exploratory visual analysis requires new methods that can be applied interactively to dynamic data. In this work, various methods that support the interactive visual analysis of biomolecular processes are introduced and discussed. The presented GPU-accelerated methods are parameterizable in real-time by the user and enable an exploratory analysis on current desktop computers. The basis for a visual exploration is the interactive visualization of complex molecular models for large, dynamic data sets without resorting to precomputed data. Consequently, this allows the user to switch between different representations without delay, which could otherwise disrupt and impair the analysis process. Hence, the user can analyze the dynamics of the simulated biomolecules. To facilitate the visual analysis, several real-time rendering methods have been developed and introduced, which for example enhance depth perception or provide a clearer, less cluttered depiction using non-photorealistic rendering. Based on these techniques, analysis methods and tools have been developed that extract complex properties of the simulated molecules. An example is the detection of cavities and channels, which play an essential role for the function of proteins. This enables analyzing the accessibility of binding sites for reactants, which can trigger an enzymatic reaction, or the permeability of a channel protein for a certain species of solvent molecules. Since the visual analysis of the simulation data is fully interactive, it supports the user not only in verifying existing hypotheses about the properties of the biomolecules but also allows for unexpected findings. Experts from the field of biochemistry have for example been able to find a channel to the binding site of a protein that did not agree with the predicted one. The combination of various analysis methods allows for a comprehensive, consistently interactive, exploratory visual analysis of biomolecular simulations, which gives users detailed insights into the data in real-time and fosters the discovery of new, unanticipated phenomena.Item Open Access Light transport simulation in participating media using spherical harmonic methods(2021) Körner, David; Eberhardt, Bernhard (Prof. Dr.)
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