kth.sePublications
Change search
Link to record
Permanent link

Direct link
Publications (10 of 102) Show all publications
Mallor, F., Liu, J., Peplinski, A., Vinuesa, R., Örlü, R., Weinkauf, T. & Schlatter, P. (2024). In-Situ Analysis of Backflow Events and Their Relation to Separation in Wings Through Well-Resolved LES. In: ERCOFTAC Series: (pp. 17-22). Springer Science and Business Media B.V., 31
Open this publication in new window or tab >>In-Situ Analysis of Backflow Events and Their Relation to Separation in Wings Through Well-Resolved LES
Show others...
2024 (English)In: ERCOFTAC Series, Springer Science and Business Media B.V. , 2024, Vol. 31, p. 17-22Chapter in book (Other academic)
Abstract [en]

Wall-bounded turbulent flows as those occurring in transportation (e.g. aviation) or industrial applications (e.g turbomachinery), are usually subjected to pressure gradients (PGs). The presence of such PGs affects greatly the development and physics of the turbulent boundary layer (TBL), making it an open research area. An important phenomena associated with the presence of strong adverse PGs (APGs) as appearing in wings, is the separation of the boundary layer, which can lead to stall.

Place, publisher, year, edition, pages
Springer Science and Business Media B.V., 2024
National Category
Fluid Mechanics and Acoustics
Identifiers
urn:nbn:se:kth:diva-340780 (URN)10.1007/978-3-031-47028-8_3 (DOI)2-s2.0-85178156992 (Scopus ID)
Note

QC 20231214

Available from: 2023-12-14 Created: 2023-12-14 Last updated: 2023-12-14Bibliographically approved
Shi, D., Oulasvirta, A., Weinkauf, T. & Cao, N. (2024). Understanding and Automating Graphical Annotations on Animated Scatterplots. In: Proceedings - 2024 IEEE 17th Pacific Visualization Conference, PacificVis 2024: . Paper presented at 17th IEEE Pacific Visualization Conference, PacificVis 2024, Tokyo, Japan, Apr 23 2024 - Apr 26 2024 (pp. 212-221). Institute of Electrical and Electronics Engineers (IEEE)
Open this publication in new window or tab >>Understanding and Automating Graphical Annotations on Animated Scatterplots
2024 (English)In: Proceedings - 2024 IEEE 17th Pacific Visualization Conference, PacificVis 2024, Institute of Electrical and Electronics Engineers (IEEE) , 2024, p. 212-221Conference paper, Published paper (Refereed)
Abstract [en]

Scatterplots are commonly used in various contexts, from scientific publications to infographics for the general public. However, not everyone is able to read them, and even experts may struggle to notice some important information such as overlapping clusters or temporal changes. To address these issues, a computational approach for annotating scatterplots has been developed. This approach involves various forms of annotation, including drawing lines to show correlations, circling areas to show clusters, and indicating movement with arrows. The approach is based on a study that identified common annotation strategies used by people to annotate scatterplots. These strategies are distilled into an automated method for generating graphical annotations on scatterplots. The method involves a problem formulation using a Markov Decision Process and a model for making annotation decisions. The model generates step-by-step graphical annotations by analyzing data insights and observing the chart. The final result conveys a narrative that is easy to understand and allows for the conveyance of temporal changes in the data. The study results suggest that the method can generate understandable and functional annotations that are comparable to those created by human experts. This approach can potentially reduce the time and effort required to read scatterplots, making it a useful tool for data visualization novices.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2024
Keywords
Annotated Visualization, Scatterplot
National Category
Computer Sciences Language Technology (Computational Linguistics)
Identifiers
urn:nbn:se:kth:diva-348781 (URN)10.1109/PacificVis60374.2024.00031 (DOI)2-s2.0-85195987460 (Scopus ID)
Conference
17th IEEE Pacific Visualization Conference, PacificVis 2024, Tokyo, Japan, Apr 23 2024 - Apr 26 2024
Note

Part of ISBN 9798350393804

QC 20240701

Available from: 2024-06-27 Created: 2024-06-27 Last updated: 2024-07-01Bibliographically approved
Jansson, N., Karp, M., Perez, A., Mukha, T., Ju, Y., Liu, J., . . . Markidis, S. (2023). Exploring the Ultimate Regime of Turbulent Rayleigh–Bénard Convection Through Unprecedented Spectral-Element Simulations. In: SC '23: Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis: . Paper presented at SC: The International Conference for High Performance Computing, Networking, Storage, and Analysis, NOV 12–17 DENVER, CO, USA (pp. 1-9). Association for Computing Machinery (ACM), Article ID 5.
Open this publication in new window or tab >>Exploring the Ultimate Regime of Turbulent Rayleigh–Bénard Convection Through Unprecedented Spectral-Element Simulations
Show others...
2023 (English)In: SC '23: Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, Association for Computing Machinery (ACM) , 2023, p. 1-9, article id 5Conference paper, Published paper (Refereed)
Abstract [en]

We detail our developments in the high-fidelity spectral-element code Neko that are essential for unprecedented large-scale direct numerical simulations of fully developed turbulence. Major inno- vations are modular multi-backend design enabling performance portability across a wide range of GPUs and CPUs, a GPU-optimized preconditioner with task overlapping for the pressure-Poisson equation and in-situ data compression. We carry out initial runs of Rayleigh–Bénard Convection (RBC) at extreme scale on the LUMI and Leonardo supercomputers. We show how Neko is able to strongly scale to 16,384 GPUs and obtain results that are not pos- sible without careful consideration and optimization of the entire simulation workflow. These developments in Neko will help resolv- ing the long-standing question regarding the ultimate regime in RBC. 

Place, publisher, year, edition, pages
Association for Computing Machinery (ACM), 2023
National Category
Computer Sciences Fluid Mechanics and Acoustics
Identifiers
urn:nbn:se:kth:diva-340333 (URN)10.1145/3581784.3627039 (DOI)2-s2.0-85179549233 (Scopus ID)
Conference
SC: The International Conference for High Performance Computing, Networking, Storage, and Analysis, NOV 12–17 DENVER, CO, USA
Funder
Swedish Research Council, 2019-04723Swedish e‐Science Research CenterEU, Horizon 2020, 101093393, 101092621, 956748
Note

Part of ISBN 9798400701092

QC 20231204

Available from: 2023-12-04 Created: 2023-12-04 Last updated: 2024-04-22Bibliographically approved
Eberhardt, F., Bushong, E. A., Phan, S., Peltier, S., Monteagudo-Mesas, P., Weinkauf, T., . . . Ellisman, M. (2022). A Uniform and Isotropic Cytoskeletal Tiling Fills Dendritic Spines. eNeuro, 9(5), Article ID ENEURO.0342-22.2022.
Open this publication in new window or tab >>A Uniform and Isotropic Cytoskeletal Tiling Fills Dendritic Spines
Show others...
2022 (English)In: eNeuro, E-ISSN 2373-2822, Vol. 9, no 5, article id ENEURO.0342-22.2022Article in journal (Refereed) Published
Abstract [en]

Dendritic spines are submicron, subcellular compartments whose shape is defined by actin filaments and associated proteins. Accurately mapping the cytoskeleton is a challenge, given the small size of its components. It remains unclear whether the actin-associated structures analyzed in dendritic spines of neurons in vitro apply to dendritic spines of intact, mature neurons in situ. Here, we combined advanced preparative methods with multitilt serial section electron microscopy (EM) tomography and computational analysis to reveal the full three-dimensional (3D) internal architecture of spines in the intact brains of male mice at nanometer resolution. We compared hippocampal (CA1) pyramidal cells and cerebellar Purkinje cells in terms of the length distribution and connectivity of filaments, their branching-angles and absolute orientations, and the elementary loops formed by the network. Despite differences in shape and size across spines and between spine heads and necks, the internal organization was remarkably similar in both neuron types and largely homogeneous throughout the spine volume. In the tortuous mesh of highly branched and interconnected filaments, branches exhibited no preferred orientation except in the immediate vicinity of the cell membrane. We found that new filaments preferentially split off from the convex side of a bending filament, consistent with the behavior of Arp2/3-mediated branching of actin under mechanical deformation. Based on the quantitative analysis, the spine cytoskeleton is likely subject to considerable mechanical force in situ. 

Place, publisher, year, edition, pages
Society for Neuroscience, 2022
Keywords
actin cytoskeleton, cerebellar Purkinje cell, dendritic spines in situ, EM tomography, hippocampal pyramidal cell, image segmentation, Actins, Animals, Cytoskeleton, Dendritic Spines, Hippocampus, Male, Mice, Neurons, ketamine, xylazine, actin, actin filament, animal cell, animal experiment, animal model, animal tissue, Article, brain tissue, C57BL/6N mouse, cell membrane, controlled study, dendritic spine, electron microscopy, electron tomography, endoplasmic reticulum, image reconstruction, machine learning, molecular dynamics, morphometry, mouse, nonhuman, postsynaptic density, Purkinje cell, pyramidal nerve cell, quantitative analysis, synapse, three dimensional echography, animal, metabolism, nerve cell
National Category
Neurosciences
Identifiers
urn:nbn:se:kth:diva-328819 (URN)10.1523/ENEURO.0342-22.2022 (DOI)36216507 (PubMedID)2-s2.0-85140624821 (Scopus ID)
Note

QC 20230613

Available from: 2023-06-13 Created: 2023-06-13 Last updated: 2023-06-13Bibliographically approved
Atzori, M., Köpp, W., Chien, W. D., Massaro, D., Mallor, F., Peplinski, A., . . . Weinkauf, T. (2022). In situ visualization of large-scale turbulence simulations in Nek5000 with ParaView Catalyst. Journal of Supercomputing, 78(3), 3605-3620
Open this publication in new window or tab >>In situ visualization of large-scale turbulence simulations in Nek5000 with ParaView Catalyst
Show others...
2022 (English)In: Journal of Supercomputing, ISSN 0920-8542, E-ISSN 1573-0484, Vol. 78, no 3, p. 3605-3620Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
Springer, 2022
Keywords
Computational fluid dynamics, High-performance computing, In situ visualization, Catalysts, Data visualization, Efficiency, Image enhancement, Scalability, Supercomputers, Visualization, Application scenario, High performance computing systems, High-fidelity simulations, High-performance simulation, Large scale turbulence, Parallel efficiency, Relative efficiency, Technical challenges, In situ processing
National Category
Computer Sciences
Identifiers
urn:nbn:se:kth:diva-311178 (URN)10.1007/s11227-021-03990-3 (DOI)000680293400003 ()35210696 (PubMedID)2-s2.0-85111797526 (Scopus ID)
Note

QC 20220502

Available from: 2022-05-02 Created: 2022-05-02 Last updated: 2024-01-19Bibliographically approved
Köpp, W. & Weinkauf, T. (2022). Temporal Merge Tree Maps: A Topology-Based Static Visualization for Temporal Scalar Data. Paper presented at IEEE VIS, Oklahoma City, USA (Hybrid), October 16-21, 2022. IEEE Transactions on Visualization and Computer Graphics, 29(1)
Open this publication in new window or tab >>Temporal Merge Tree Maps: A Topology-Based Static Visualization for Temporal Scalar Data
2022 (English)In: IEEE Transactions on Visualization and Computer Graphics, ISSN 1077-2626, E-ISSN 1941-0506, Vol. 29, no 1Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2022
Keywords
Data Visualization, Scalar field visualization, Augmented merge tree, Pixel-based visualization
National Category
Computer Sciences
Research subject
Computer Science; SRA - E-Science (SeRC)
Identifiers
urn:nbn:se:kth:diva-320651 (URN)10.1109/TVCG.2022.3209387 (DOI)36155442 (PubMedID)2-s2.0-85139464273 (Scopus ID)
Conference
IEEE VIS, Oklahoma City, USA (Hybrid), October 16-21, 2022
Funder
Swedish e‐Science Research CenterSwedish Foundation for Strategic Research, BD15-0082
Note

QC 20221201

Available from: 2022-10-29 Created: 2022-10-29 Last updated: 2023-06-08Bibliographically approved
Preuss, D., Weinkauf, T. & Krueger, J. (2021). A Discrete Probabilistic Approach to Dense Flow Visualization. IEEE Transactions on Visualization and Computer Graphics, 27(12), 4347-4358
Open this publication in new window or tab >>A Discrete Probabilistic Approach to Dense Flow Visualization
2021 (English)In: IEEE Transactions on Visualization and Computer Graphics, ISSN 1077-2626, E-ISSN 1941-0506, Vol. 27, no 12, p. 4347-4358Article in journal (Refereed) Published
Abstract [en]

Dense flow visualization is a popular visualization paradigm. Traditionally, the various models and methods in this area use a continuous formulation, resting upon the solid foundation of functional analysis. In this work, we examine a discrete formulation of dense flow visualization. From probability theory, we derive a similarity matrix that measures the similarity between different points in the flow domain, leading to the discovery of a whole new class of visualization models. Using this matrix, we propose a novel visualization approach consisting of the computation of spectral embeddings, i.e., characteristic domain maps, defined by particle mixture probabilities. These embeddings are scalar fields that give insight into the mixing processes of the flow on different scales. The approach of spectral embeddings is already well studied in image segmentation, and we see that spectral embeddings are connected to Fourier expansions and frequencies. We showcase the utility of our method using different 2D and 3D flows.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2021
Keywords
Complexity theory, Technological innovation, Organizations, Collaboration, Bibliographies, Decision making, Industrial engineering, Flow visualization, volume visualization, spectral methods
National Category
Computer Sciences
Identifiers
urn:nbn:se:kth:diva-305107 (URN)10.1109/TVCG.2020.3006995 (DOI)000711642800002 ()32746273 (PubMedID)2-s2.0-85118371718 (Scopus ID)
Note

QC 20211122

Available from: 2021-11-22 Created: 2021-11-22 Last updated: 2022-06-25Bibliographically approved
Atzori, M., Köpp, W., Chien, W. D., Massaro, D., Mallor, F., Peplinski, A., . . . Weinkauf, T. (2021). In-situ visualization of large-scale turbulence simulations in Nek5000 with ParaView Catalyst.
Open this publication in new window or tab >>In-situ visualization of large-scale turbulence simulations in Nek5000 with ParaView Catalyst
Show others...
2021 (English)Report (Other academic)
Abstract [en]

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.

National Category
Mechanical Engineering
Research subject
Engineering Mechanics
Identifiers
urn:nbn:se:kth:diva-295679 (URN)
Funder
Swedish Foundation for Strategic Research , BD15-0082European Commission, 800999 (SAGE2)
Note

QC 20210525

Available from: 2021-05-25 Created: 2021-05-25 Last updated: 2024-03-15Bibliographically approved
Köpp, W., Friederici, A., Atzori, M., Vinuesa, R., Schlatter, P. & Weinkauf, T. (2021). Notes on Percolation Analysis of Sampled Scalar Fields. In: Ingrid Hotz, Talha Bin Masood, Filip Sadlo, Julien Tierny (Ed.), Topological Methods in Data Analysis and Visualization VI: Theory, Applications, and Software. Paper presented at 8th Workshop on Topological Methods in Data Analysis and Visualization, TopoInVis 2019, Nyköping, 17 June 2019 to 19 June 2019 (pp. 39-54). Springer Nature
Open this publication in new window or tab >>Notes on Percolation Analysis of Sampled Scalar Fields
Show others...
2021 (English)In: Topological Methods in Data Analysis and Visualization VI: Theory, Applications, and Software / [ed] Ingrid Hotz, Talha Bin Masood, Filip Sadlo, Julien Tierny, Springer Nature , 2021, p. 39-54Conference paper, Published paper (Refereed)
Abstract [en]

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.

Place, publisher, year, edition, pages
Springer Nature, 2021
Series
Mathematics and Visualization, ISSN 1612-3786, E-ISSN 2197-666X
Keywords
Critical value, Infinite graph, Largest connected component, Normalisation, Percolation analysis, Scalar fields, Sharp transition, Spatial correlations, Transition widths
National Category
Other Mathematics Computer Sciences
Research subject
SRA - E-Science (SeRC); Computer Science
Identifiers
urn:nbn:se:kth:diva-312324 (URN)10.1007/978-3-030-83500-2_3 (DOI)2-s2.0-85116740725 (Scopus ID)
Conference
8th Workshop on Topological Methods in Data Analysis and Visualization, TopoInVis 2019, Nyköping, 17 June 2019 to 19 June 2019
Funder
Swedish Foundation for Strategic Research, BD15-0082Swedish e‐Science Research Center
Note

QC 20221005

Available from: 2022-05-23 Created: 2022-05-23 Last updated: 2022-12-01Bibliographically approved
Lukasczyk, J., Beran, J., Engelke, W., Falk, M., Friederici, A., Garth, C., . . . Tierny, J. (2021). Report of the TopoInVis TTK Hackathon: Experiences, Lessons Learned, and Perspectives. In: Mathematics and Visualization: . Paper presented at 8th Workshop on Topological Methods in Data Analysis and Visualization, TopoInVis, Nyköping, 17 June 2019 to 19 June 2019 (pp. 359-373). Springer Nature
Open this publication in new window or tab >>Report of the TopoInVis TTK Hackathon: Experiences, Lessons Learned, and Perspectives
Show others...
2021 (English)In: Mathematics and Visualization, Springer Nature , 2021, p. 359-373Conference paper, Published paper (Refereed)
Abstract [en]

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.

Place, publisher, year, edition, pages
Springer Nature, 2021
Keywords
Software design, Current limitation, Data analysis algorithms, Development directions, Paper documents, Research communities, Topology
National Category
Computational Mathematics
Identifiers
urn:nbn:se:kth:diva-312323 (URN)10.1007/978-3-030-83500-2_18 (DOI)2-s2.0-85116762856 (Scopus ID)
Conference
8th Workshop on Topological Methods in Data Analysis and Visualization, TopoInVis, Nyköping, 17 June 2019 to 19 June 2019
Note

Part of proceedings: ISBN 978-3-030-83499-9

QC 20220523

Available from: 2022-05-23 Created: 2022-05-23 Last updated: 2023-01-17Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0002-1498-9062

Search in DiVA

Show all publications