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Dipl.-Inf. Marco Ament |
Research: |
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| Direct Volume Rendering (Opacity Models, Sampling and Reconstruction, Parallelization) | |
| Global Volume Illumination (Monte Carlo Simulation, Astronomical Visualization) | |
| High Performance Computing on GPUs (CUDA) | |
| Physically-based Simulations (Fluid Dynamics) and Visualizations (Flow Visualization) | |
| Numerical Solution of Ordinary and Partial Differential Equations |
Projects: |
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Photo-realistic and Interactive Visualization of Astronomical Objects for Digital Planetariums Abstract: This DFG-funded project aims to model astrophysical objects physically consistent for lifelike and fast 3D visualization. Therefore, methods and algorithms are developed to reconstruct the spatial structure of various objects from astronomical observations and physical constraints to visualize them interactively with modern, high-resolution planetarium displays. Cosmological effects are visualized based on scientific facts in an accessible manner for the public. |
| Publications: | |||||||||||
| 2012 | |||||||||||
Abstract:
Interactive visualization and simulation of
astrophysical phenomena enable digital planetariums and television
documentaries
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Abstract:
This paper presents a new general-relativistic ray
tracer that enables image synthesis on an interactive basis by exploiting
the |
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2011 |
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Abstract: We present an exemplary steering system that performs 2D flow simulation and visualization on graphics processing units (GPUs). The topology of a vector field provides the overall structure and therefore lends itself for steering purposes. We build on the concept of Lagrangian coherent structures present as ridges in the finite-time Lyapunov exponent (FTLE). This allows to perform steering with respect to the true time-dependent dynamics in a given time scope. Based on the insights from the FTLE visualization, our CUDA-based implementation allows effective interactive manipulation of boundary conditions such as solid obstacles or velocity profiles.
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Abstract: Sort first distributions have been studied and used far less than sort last distributions for parallel volume rendering, especially when the data is too large to be replicated fully. We demonstrate that sort first distributions are not only a viable method of performing data scalable parallel volume rendering, but more importantly they allow for a range of rendering algorithms and techniques that are not efficient with sort last distributions. Several of these algorithms are discussed and two of them are implemented in a parallel environment: a new improved variant of early ray termination to speed up rendering when volumetric occlusion occurs and a volumetric shadowing technique that produces more realistic and informative images based on half angle slicing. Improved methods of distributing the computation of the load balancing and loading portions of a subdivided data set are also presented. Our detailed test results for a typical GPU cluster with distributed memory show that our sort first rendering algorithm outperforms sort last rendering in many scenarios. |
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2010 |
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Abstract: We extend direct volume rendering with a unified model for generalized isosurfaces, also called interval volumes, allowing a wider spectrum of visual classification. We generalize the concept of scale-invariant opacity—typical for isosurface rendering—to semi-transparent interval volumes. Scale-invariant rendering is independent of physical space dimensions and therefore directly facilitates the analysis of data characteristics. Our model represents sharp isosurfaces as limits of interval volumes and combines them with features of direct volume rendering. Our objective is accurate rendering, guaranteeing that all isosurfaces and interval volumes are visualized in a crack-free way with correct spatial ordering. We achieve simultaneous direct and interval volume rendering by extending preintegration and explicit peak finding with data-driven splitting of ray integration and hybrid computation in physical and data domains. Our algorithm is suitable for efficient parallel processing for interactive applications as demonstrated by our CUDA implementation.
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Abstract: We present a parallel conjugate gradient solver for the Poisson problem optimized for multi-GPU platforms. Our approach includes a novel heuristic Poisson preconditioner which is well-suited for massively-parallel SIMD processing. Furthermore, we address the problem of limited transfer rates over typical data channels such as the PCI-express bus relative to the bandwidth requirements of powerful GPUs. Specifically, naïve communication schemes can severely reduce the achievable speedup in such communication-intense algorithms. For this reason, we employ overlapping memory transfers to establish a high level of concurrency and to improve scalability. We have implemented our model on a high-performance workstation with multiple hardware accelerators. We will discuss the mathematical principles, give implementation details, and present the performance and the scalability of the system. |
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2009 |
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Abstract: We present a physically-based fluid simulation with dynamic grid refinement on parallel SIMD graphics hardware. The irregular and dynamic structure of an adaptive grid requires sophisticated memory access patterns as well as a decomposition of the problem for parallel processing and the distribution of tasks to multiple threads. In this paper, we focus on the representation and management of the dynamic grid on the graphics device for an efficient parallelization of the advection step and the iterative solving of the Poisson equation. In order to achieve high performance, we utilize the hardware’s capabilities like fast cache access and trilinear filtering. Furthermore, expensive data transfer between host and device is minimized to avoid a major bottleneck. We report results on the inherent overhead of the dynamic grid compared to an equivalent Cartesian grid. In addition, a visual simulation of smoke is presented with radiosity-based illumination and volume ray casting at interactive frame rates. |
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2008 |
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Abstract: In this thesis, a physically-based fluid simulation with dynamic grid refinement parallel SIMD graphics hardware is presented. The irregular and dynamic structure of an adaptive grid requires sophisticated memory access patterns as well as a decomposition of the problem for parallel processing and the distribution of tasks to multiple threads. The focus of this thesis lies on the representation and management of the dynamic grid on the graphics device for an efficient parallelization of the advection step and the iterative solving of the Poisson equation. In order to achieve high performance, the hardware's capabilities like fast cache access and trilinear filtering are utilized. Furthermore, expensive data transfer between host and device is minimized to avoid a major bottleneck. Results on the inherent overhead of the dynamic grid compared to an equivalent Cartesian grid are reported. In addition, a visual simulation of smoke is presented with radiosity-based illumination and volume ray casting at interactive frame rates. |
Advised Thesis: |
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| 2009 | Diplomarbeit: Parallele Berechnungen der volumetrischen Beleuchtung astrophysikalischer Nebel auf GPU-Clustern
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| 2010 | Diplomarbeit: Globale volumetrische Beleuchtung mit hierarchischer Mehrfachstreuung in partizipierenden Medien Studienarbeit: Globale Volumenbeleuchtung mit Photon Mapping und Path Tracing
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| 2011 | Diplomarbeit:
Texturadvektion
höherer Ordnung (finished) |
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| 2012 | BSc-Arbeit:
Visualisierung von planetarischen Nebeln in
Celestia (running...) |
Teaching: |
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| WS 09/10 | Übungen zur Vorlesung Modellierung und Animation Studienprojekt Stellarkartographie Informatiktag 2010 - Visualisierung von Fraktalen
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| SS 10 | Studienprojekt Stellarkartographie | |
| WS 10/11 | Übungen zur Vorlesung Modellierung und Animation | |
| SS 11 | Hauptseminar
Visualisierung großer Datensätze Tag der Wissenschaft 2011 - Interaktive Visualisierung | Strömungssimulation |
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| WS 11/12 | Hauptseminar Volumenrendering | |
| SS 12 | Übungen zur Vorlesung Bildsynthese |
Short CV: |
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| 2000 | Abitur at Gymnasium Plochingen. | |
| 2000-2001 | Civil service at Johanniterstift Plochingen. | |
| 2001-2002 | Professional training in cycling and holder of class-A licence. |
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| 2002-2009 | Study of computer science with physics as a minor subject at University of Tübingen. |
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| 2009-present | Research Assistant at University of Stuttgart. PhD Student at VISUS (Prof. Weiskopf). |