| 1. |
- Atzori, Marco, et al.
(författare)
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In-situ visualization of large-scale turbulence simulations in Nek5000 with ParaView Catalyst
- 2021
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- In-situ visualization on HPC systems allows us to analyze simulation results that would otherwise be impossible, given the size of the simulation data sets and offline post-processing execution time. We design and develop in-situ visualization with Paraview Catalyst in Nek5000, a massively parallel Fortran and C code for computational fluid dynamics applications. We perform strong scalability tests up to 2,048 cores on KTH's Beskow Cray XC40 supercomputer and assess in-situ visualization's impact on the Nek5000 performance. In our study case, a high-fidelity simulation of turbulent flow, we observe that in-situ operations significantly limit the strong scalability of the code, reducing the relative parallel efficiency to only ~21\% on 2,048 cores (the relative efficiency of Nek5000 without in-situ operations is ~99\%). Through profiling with Arm MAP, we identified a bottleneck in the image composition step (that uses Radix-kr algorithm) where a majority of the time is spent on MPI communication. We also identified an imbalance of in-situ processing time between rank 0 and all other ranks. Better scaling and load-balancing in the parallel image composition would considerably improve the performance and scalability of Nek5000 with in-situ capabilities in large-scale simulation.
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| 2. |
- Atzori, Marco, 1992-, et al.
(författare)
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In situ visualization of large-scale turbulence simulations in Nek5000 with ParaView Catalyst
- 2022
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Ingår i: Journal of Supercomputing. - : Springer. - 0920-8542 .- 1573-0484. ; 78:3, s. 3605-3620
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Tidskriftsartikel (refereegranskat)abstract
- In situ visualization on high-performance computing systems allows us to analyze simulation results that would otherwise be impossible, given the size of the simulation data sets and offline post-processing execution time. We develop an in situ adaptor for Paraview Catalyst and Nek5000, a massively parallel Fortran and C code for computational fluid dynamics. We perform a strong scalability test up to 2048 cores on KTH’s Beskow Cray XC40 supercomputer and assess in situ visualization’s impact on the Nek5000 performance. In our study case, a high-fidelity simulation of turbulent flow, we observe that in situ operations significantly limit the strong scalability of the code, reducing the relative parallel efficiency to only ≈ 21 % on 2048 cores (the relative efficiency of Nek5000 without in situ operations is ≈ 99 %). Through profiling with Arm MAP, we identified a bottleneck in the image composition step (that uses the Radix-kr algorithm) where a majority of the time is spent on MPI communication. We also identified an imbalance of in situ processing time between rank 0 and all other ranks. In our case, better scaling and load-balancing in the parallel image composition would considerably improve the performance of Nek5000 with in situ capabilities. In general, the result of this study highlights the technical challenges posed by the integration of high-performance simulation codes and data-analysis libraries and their practical use in complex cases, even when efficient algorithms already exist for a certain application scenario.
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| 3. |
- Friederici, Anke, 1994-, et al.
(författare)
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Distributed Percolation Analysis for Turbulent Flows
- 2019
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Ingår i: 2019 IEEE 9th Symposium on Large Data Analysis and Visualization, LDAV 2019. - : Institute of Electrical and Electronics Engineers (IEEE). - 9781728126050 ; , s. 42-51
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Konferensbidrag (refereegranskat)abstract
- Percolation analysis is a valuable tool to study the statistical properties of turbulent flows. It is based on computing the percolation function for a derived scalar field, thereby quantifying the relative volume of the largest connected component in a superlevel set for a decreasing threshold. We propose a novel memory-distributed parallel algorithm to finely sample the percolation function. It is based on a parallel version of the union-find algorithm interleaved with a global synchronization step for each threshold sample. The efficiency of this algorithm stems from the fact that operations in-between threshold samples can be freely reordered, are mostly local and thus require no inter-process communication. Our algorithm is significantly faster than previous algorithms for this purpose, and is neither constrained by memory size nor number of compute nodes compared to the conceptually related algorithm for extracting augmented merge trees. This makes percolation analysis much more accessible in a large range of scenarios. We explore the scaling of our algorithm for different data sizes, number of samples and number of MPI processes. We demonstrate the utility of percolation analysis using large turbulent flow data sets.
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| 4. |
- Köpp, Wiebke, 1989-, et al.
(författare)
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Notes on Percolation Analysis of Sampled Scalar Fields
- 2019
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Percolation analysis is used to explore the connectivity of randomly connected infinite graphs. In the finite case, a closely related percolation function captures the relative volume of the largest connected component in a scalar field's-super level set. While prior work has shown that random scalar fields with little spatial correlation yield a sharp transition in this function, little is known about its behavior on real data. In this work, we explore how different characteristics of a scalar field – such as its histogram or degree of structure – influence the shape of the percolation function. We estimate the critical value and transition width of the percolation function, and propose a corresponding normalization scheme that relates these values to known results on infinite graphs. In our experiments, we find that percolation analysis can be used to analyze the degree of structure in Gaussian random fields. On a simulated turbulent duct flow data set we observe that the critical values are stable and consistent across time. Our normalization scheme indeed aid comparison between data sets and relation to infinite graphs.
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| 5. |
- Köpp, Wiebke, 1989-, et al.
(författare)
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Notes on Percolation Analysis of Sampled Scalar Fields
- 2021
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Ingår i: Topological Methods in Data Analysis and Visualization VI. - Cham : Springer Nature. ; , s. 39-54
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Konferensbidrag (refereegranskat)abstract
- Percolation analysis is used to explore the connectivity of randomly connected infinite graphs. In the finite case, a closely related percolation function captures the relative volume of the largest connected component in a scalar field’s superlevel set. While prior work has shown that random scalar fields with little spatial correlation yield a sharp transition in this function, little is known about its behavior on real data. In this work, we explore how different characteristics of a scalar field—such as its histogram or degree of structure—influence the shape of the percolation function. We estimate the critical value and transition width of the percolation function, and propose a corresponding normalization scheme that relates these values to known results on infinite graphs. In our experiments, we find that percolation analysis can be used to analyze the degree of structure in Gaussian random fields. On a simulated turbulent duct flow data set we observe that the critical values are stable and consistent across time. Our normalization scheme indeed aids comparison between data sets and relation to infinite graphs.
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| 6. |
- Köpp, Wiebke, 1989-
(författare)
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Static Visualizations for Dynamic Hierarchies
- 2022
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Dynamic hierarchical data describes phenomena in a wide range of domains, from file management to demographics and business administration, as well as feature extraction results in spatial scientific data. As with all data, visualization is an integral step for gaining understanding about dynamic hierarchical data. In contrast to the visualization of individual static hierarchies, the visualization of dynamic hierarchies comes with additional challenges since many different aspects of a hierarchy may be subject to change.This thesis presents novel visualizations, compact data structures, and layout optimizations for dynamic hierarchies where both topology and data may change. Particular focus is placed on the type of hierarchies that stem from features in scalar fields, namely merge trees and derived discretized feature hierarchies. We propose several visualization schemes that summarize dynamic hierarchies statically by creating stacked one-dimensional representations. The stacking dimension corresponds to the data’s dynamic-inducing variable which is usually time. In contrast to animating individual visualizations for each variable setting or time step, our static overviews of the entirety of the data facilitate comparison both between multiple data sets and across the stacking dimension. For the preservation of a user’s mental map, we utilize correspondences between parts of the hierarchy to optimize the one-dimensional representations toward stability in regards to the dynamic-inducing dimension. To evaluate our proposed methods, we apply them to several real-world data sets, compare them against existing approaches, and study how the resulting visualizations are affected by method parameters.
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| 7. |
- Köpp, Wiebke, 1989-, et al.
(författare)
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Temporal Merge Tree Maps: A Topology-Based Static Visualization for Temporal Scalar Data
- 2022
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Ingår i: IEEE Transactions on Visualization and Computer Graphics. - : Institute of Electrical and Electronics Engineers (IEEE). - 1077-2626 .- 1941-0506. ; 29:1
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Tidskriftsartikel (refereegranskat)abstract
- Creating a static visualization for a time-dependent scalar field is a non-trivial task, yet very insightful as it shows the dynamics in one picture. Existing approaches are based on a linearization of the domain or on feature tracking. Domain linearizations use space-filling curves to place all sample points into a 1D domain, thereby breaking up individual features. Feature tracking methods explicitly respect feature continuity in space and time, but generally neglect the data context in which those features live. We present a feature-based linearization of the spatial domain that keeps features together and preserves their context by involving all data samples. We use augmented merge trees to linearize the domain and show that our linearized function has the same merge tree as the original data. A greedy optimization scheme aligns the trees over time providing temporal continuity. This leads to a static 2D visualization with one temporal dimension, and all spatial dimensions compressed into one. We compare our method against other domain linearizations as well as feature-tracking approaches, and apply it to several real-world data sets.
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| 8. |
- Köpp, Wiebke, 1989-, et al.
(författare)
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Temporal Treemaps: Static Visualization of Evolving Trees
- 2019
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Ingår i: IEEE Transactions on Visualization and Computer Graphics. - : IEEE Computer Society. - 1077-2626 .- 1941-0506. ; 25:1, s. 534-543
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Tidskriftsartikel (refereegranskat)abstract
- We consider temporally evolving trees with changing topology and data: tree nodes may persist for a time range, merge or split, and the associated data may change. Essentially, one can think of this as a time series of trees with a node correspondence per hierarchy level between consecutive time steps. Existing visualization approaches for such data include animated 2D treemaps, where the dynamically changing layout makes it difficult to observe the data in its entirety. We present a method to visualize this dynamic data in a static, nested, and space-filling visualization. This is based on two major contributions: First, the layout constitutes a graph drawing problem. We approach it for the entire time span at once using a combination of a heuristic and simulated annealing. Second, we propose a rendering that emphasizes the hierarchy through an adaption of the classic cushion treemaps. We showcase the wide range of applicability using data from feature tracking in time-dependent scalar fields, evolution of file system hierarchies, and world population.
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| 9. |
- Lukasczyk, J., et al.
(författare)
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Report of the TopoInVis TTK Hackathon : Experiences, Lessons Learned, and Perspectives
- 2021
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Ingår i: Mathematics and Visualization. - Cham : Springer Nature. ; , s. 359-373, s. 359-373
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Konferensbidrag (refereegranskat)abstract
- This paper documents the organization, the execution, and the results of the Topology ToolKit (TTK) hackathon that took place at the TopoInVis 2019 conference. The primary goal of the hackathon was to promote TTK in our research community as a unified software development platform for topology-based data analysis algorithms. To this end, participants were first introduced to the structure and capabilities of TTK, and then worked on their own TTK-related projects while being mentored by senior TTK developers. Notable outcomes of the hackathon were first steps towards Python and Docker packages, further integration of TTK in Inviwo, the extension of TTK with new algorithms, and the discovery of current limitations of TTK as well as future development directions.
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