EGPGV: Eurographics Workshop on Parallel Graphics and Visualization
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Browsing EGPGV: Eurographics Workshop on Parallel Graphics and Visualization by Author "Garth, Christoph"
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Item Alternative Parameters for On-The-Fly Simplification of MergeTrees(The Eurographics Association, 2020) Werner, Kilian; Garth, Christoph; Frey, Steffen and Huang, Jian and Sadlo, FilipTopological simplification of merge trees requires a user specified persistence threshold. As this threshold is based on prior domain knowledge and has an unpredictable relation to output size, its use faces challenges in large-data situations like online, distributed or out-of-core scenarios. We propose two alternative parameters, a targeted percentile size reduction and a total output size limit, to increase flexibility in those scenarios.Item Extended Visual Programming for Complex Parallel Pipelines in ParaView(The Eurographics Association, 2023) Petersen, Marvin; Lukasczyk, Jonas; Gueunet, Charles; Chabat, Timothée; Garth, Christoph; Bujack, Roxana; Pugmire, David; Reina, GuidoModern visualization software facilitates the creation of visualization pipelines combining a plethora of algorithms to achieve high-fidelity visualization. When the complexity of the pipelines to be created increases, additional techniques are needed to ensure that reasoning about the pipelines structure and its performance remains feasible. This paper presents three additions to ParaView with the goal of improving presentation of complex, parallel pipelines benefiting pipeline realization. More specifically, we provide a runtime performance annotation visualization integrated in a visual programming node editor, allowing all users to reason about basic performance and intuitively manipulate the structure and configuration of pipelines. Further, we extend the list of available filters with control flow filters, supporting for- and while-loops with a comprehensible representation in the node editor. Our extension is based on graphical manipulation of a node graph that expresses the flow of data and computation in a VTK pipeline, and draws upon a long tradition and positive experience with similar interfaces across a wide range of software systems such as the visualization tools SCIRun and VTK Designer, or the rendering systems Blender and Houdini. The extension we provide integrates seamlessly into the existing ParaView architecture as a plug-in, i.e., it does not require any modifications to ParaView itself or VTK's execution model.Item 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, FilipIn 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.