DSpace Repository :: Browsing by Author "Bujack, Roxana"

Browsing by Author "Bujack, Roxana"

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Approaches for In Situ Computation of Moments in a Data-Parallel Environment
(The Eurographics Association, 2020) Tsai, Karen C.; Bujack, Roxana; Geveci, Berk; Ayachit, Utkarsh; Ahrens, James; Frey, Steffen and Huang, Jian and Sadlo, Filip
Feature-driven in situ data reduction can overcome the I/O bottleneck that large simulations face in modern supercomputer architectures in a semantically meaningful way. In this work, we make use of pattern detection as a black box detector of arbitrary feature templates of interest. In particular, we use moment invariants because they allow pattern detection independent of the specific orientation of a feature. We provide two open source implementations of a rotation invariant pattern detection algorithm for high performance computing (HPC) clusters with a distributed memory environment. The first one is a straightforward integration approach. The second one makes use of the Fourier transform and the Cross-Correlation Theorem. In this paper, we will compare the two approaches with respect to performance and flexibility and showcase results of the in situ integration with real world simulation code.
Automatic Improvement of Continuous Colormaps in Euclidean Colorspaces
(The Eurographics Association and John Wiley & Sons Ltd., 2021) Nardini, Pascal; Chen, Min; Böttinger, Michael; Scheuermann, Gerik; Bujack, Roxana; Borgo, Rita and Marai, G. Elisabeta and Landesberger, Tatiana von
Colormapping is one of the simplest and most widely used data visualization methods within and outside the visualization community. Uniformity, order, discriminative power, and smoothness of continuous colormaps are the most important criteria for evaluating and potentially improving colormaps. We present a local and a global automatic optimization algorithm in Euclidean color spaces for each of these design rules in this work. As a foundation for our optimization algorithms, we used the CCC-Tool colormap specification (CMS); each algorithm has been implemented in this tool. In addition to synthetic examples that demonstrate each method's effect, we show the outcome of some of the methods applied to a typhoon simulation.
EnVirVis 2017: Frontmatter
(Eurographics Association, 2017) Rink, Karsten; Middel, Ariane; Zeckzer, Dirk; Bujack, Roxana;
EnvirVis 2019: Frontmatter
(The Eurographics Association, 2019) Bujack, Roxana; Feige, Kathrin; Rink, Karsten; Zeckzer, Dirk; Bujack, Roxana and Feige, Kathrin and Rink, Karsten and Zeckzer, Dirk
EuroVis 2023 CGF 42-3: Frontmatter
(The Eurographics Association and John Wiley & Sons Ltd., 2023) Bujack, Roxana; Archambault, Daniel; Schreck, Tobias; Bujack, Roxana; Archambault, Daniel; Schreck, Tobias
EuroVis 2024 CGF 43-3: Frontmatter
(The Eurographics Association and John Wiley & Sons Ltd., 2024) Aigner, Wolfgang; Archambault, Daniel; Bujack, Roxana; Aigner, Wolfgang; Archambault, Daniel; Bujack, Roxana
An Interpolation Scheme for VDVP Lagrangian Basis Flows
(The Eurographics Association, 2019) Sane, Sudhanshu; Childs, Hank; Bujack, Roxana; Childs, Hank and Frey, Steffen
Using the Eulerian paradigm, accurate flow visualization of 3D time-varying data requires a high temporal resolution resulting in large storage requirements. The Lagrangian paradigm has proven to be a viable in situ-based approach to tackle this large data visualization problem. However, previous methods constrained the generation of Lagrangian basis flows to the special case of fixed duration and fixed placement (FDFP), in part because reconstructing the flow field using these basis flows is trivial. Our research relaxes this constraint, by considering the general case of variable duration and variable placement (VDVP) with the goal of increasing the amount of information per byte stored. That said, reconstructing the flow field using VDVP basis flows is non-trivial; the primary contribution of our work is a method we call VDVP-Interpolation which solves this problem. VDVP-Interpolation reduces error propagation and limits interpolation error while using VDVP Lagrangian basis flows. As a secondary contribution of the work, we generate VDVP basis flows for multiple data sets and demonstrate improved accuracy-storage propositions compared to previous work. In some cases, we demonstrate up to 40-60% more accurate pathline calculation while using 50% less data storage.
Leveraging Lagrangian Analysis for Discriminating Nutrient Origins
(The Eurographics Association, 2019) Dutta, Soumya; Brady, Riley X.; Maltrud, Mathew E.; Wolfram, Philip J.; Bujack, Roxana; Bujack, Roxana and Feige, Kathrin and Rink, Karsten and Zeckzer, Dirk
Understanding the origins of nutrients, e.g., nitrate, in ocean water is essential to develop an effective mariculture technique for free-floating macroalgae, which presents a potential solution to provide an alternative source of domestic renewable fuels to help reduce carbon emissions from automobiles. To study this problem, scientists simulate large-scale computational simulations with coupled flow and nutrient information. Since running the simulation multiple times is expensive, the scientists want to have efficient visual-analytic techniques that can analyze and visualize the simulation output quickly to investigate the reasons behind the existence of nitrate in different areas of ocean water. To address these needs, a mixed Lagrangian and Eulerianbased analysis technique is developed that leverages traditional Lagrangian analysis methods and fuses Eulerian information with it to comprehend the origins of nutrients in the water. The proposed method yielded promising results for the application scientists and positive feedback from them demonstrates the efficacy of the technique.
Objective Finite-Time Saddles and their Connection to FTLE
(The Eurographics Association, 2019) Bujack, Roxana; Dutta, Soumya; Rojo, Irene Baeza; Zhang, Duan; Günther, Tobias; Johansson, Jimmy and Sadlo, Filip and Marai, G. Elisabeta
Based on an intuitive physical definition of what a finite-time saddle-like behavior is, we derive a mathematical definition. We show that this definition builds the link between two FTLE-based saddle generalizations, which is not only of theoretical interest but also provides a more robust extraction of finite-time saddles.
PGV 2022: Frontmatter
(The Eurographics Association, 2022) Bujack, Roxana; Tierny, Julien; Sadlo, Filip; Bujack, Roxana; Tierny, Julien; Sadlo, Filip
PGV 2023: Frontmatter
(The Eurographics Association, 2023) Bujack, Roxana; Pugmire, David; Reina, Guido; Bujack, Roxana; Pugmire, David; Reina, Guido
Robust Cut for Hierarchical Clustering and Merge Trees
(The Eurographics Association, 2024) Banesh, Divya; Ahrens, James; Bujack, Roxana; Tominski, Christian; Waldner, Manuela; Wang, Bei
Hierarchical clustering arrange multi-dimensional data into a tree-like structure, organizing the data by increasing levels of similarity. A cut of the tree divides data into clusters, where cluster members share a likeness. Most common cutting techniques identify a single line, either by a metric or with user input, cutting horizontally through the tree, separating root from leaves. We present a new approach that algorithmically identifies cuts at multiple levels of the tree based on a metric we call robustness. We identify levels to maximize overall robustness by maximizing the height of the shortest branch of the hierarchical tree we must cut through. This technique minimizes the variation within clusters while maximizing the distance between clusters. We apply the same approach to merge trees from computational topology to find the most robust number of connected components. We apply the multi-level robust cut to two datasets to highlight the advantages compared to a traditional, single-level cut.
Scalable In Situ Computation of Lagrangian Representations via Local Flow Maps
(The Eurographics Association, 2021) Sane, Sudhanshu; Yenpure, Abhishek; Bujack, Roxana; Larsen, Matthew; Moreland, Kenneth; Garth, Christoph; Johnson, Chris R.; Childs, Hank; Larsen, Matthew and Sadlo, Filip
In situ computation of Lagrangian flow maps to enable post hoc time-varying vector field analysis has recently become an active area of research. However, the current literature is largely limited to theoretical settings and lacks a solution to address scalability of the technique in distributed memory. To improve scalability, we propose and evaluate the benefits and limitations of a simple, yet novel, performance optimization. Our proposed optimization is a communication-free model resulting in local Lagrangian flow maps, requiring no message passing or synchronization between processes, intrinsically improving scalability, and thereby reducing overall execution time and alleviating the encumbrance placed on simulation codes from communication overheads. To evaluate our approach, we computed Lagrangian flow maps for four time-varying simulation vector fields and investigated how execution time and reconstruction accuracy are impacted by the number of GPUs per compute node, the total number of compute nodes, particles per rank, and storage intervals. Our study consisted of experiments computing Lagrangian flow maps with up to 67M particle trajectories over 500 cycles and used as many as 2048 GPUs across 512 compute nodes. In all, our study contributes an evaluation of a communication-free model as well as a scalability study of computing distributed Lagrangian flow maps at scale using in situ infrastructure on a modern supercomputer.
State of the Art in Time-Dependent Flow Topology: Interpreting Physical Meaningfulness Through Mathematical Properties
(The Eurographics Association and John Wiley & Sons Ltd., 2020) Bujack, Roxana; Yan, Lin; Hotz, Ingrid; Garth, Christoph; Wang, Bei; Smit, Noeska and Oeltze-Jafra, Steffen and Wang, Bei
We present a state-of-the-art report on time-dependent flow topology. We survey representative papers in visualization and provide a taxonomy of existing approaches that generalize flow topology from time-independent to time-dependent settings. The approaches are classified based upon four categories: tracking of steady topology, reference frame adaption, pathline classification or clustering, and generalization of critical points. Our unique contributions include introducing a set of desirable mathematical properties to interpret physical meaningfulness for time-dependent flow visualization, inferring mathematical properties associated with selective research papers, and utilizing such properties for classification. The five most important properties identified in the existing literature include coincidence with the steady case, induction of a partition within the domain, Lagrangian invariance, objectivity, and Galilean invariance.
A Survey of Seed Placement and Streamline Selection Techniques
(The Eurographics Association and John Wiley & Sons Ltd., 2020) Sane, Sudhanshu; Bujack, Roxana; Garth, Christoph; Childs, Hank; Smit, Noeska and Oeltze-Jafra, Steffen and Wang, Bei
Streamlines are an extensively utilized flow visualization technique for understanding, verifying, and exploring computational fluid dynamics simulations. One of the major challenges associated with the technique is selecting which streamlines to display. Using a large number of streamlines results in dense, cluttered visualizations, often containing redundant information and occluding important regions, whereas using a small number of streamlines could result in missing key features of the flow. Many solutions to select a representative set of streamlines have been proposed by researchers over the past two decades. In this state-of-the-art report, we analyze and classify seed placement and streamline selection (SPSS) techniques used by the scientific flow visualization community. At a high-level, we classify techniques into automatic and manual techniques, and further divide automatic techniques into three strategies: density-based, feature-based, and similarity-based. Our analysis evaluates the identified strategy groups with respect to focus on regions of interest, minimization of redundancy, and overall computational performance. Finally, we consider the application contexts and tasks for which SPSS techniques are currently applied and have potential applications in the future.

Browsing by Author "Bujack, Roxana"

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