Steffen Frey
Visualization Research Institute, University of Stuttgart

Room 00.110
Allmandring 19
70569 Stuttgart
Tel.: +49 (0)711 685-88629
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Taken during my visit of Kwan-Liu Ma's group
at the University of California, Davis

The purpose of scientific visualization is to graphically illustrate scientific data, enabling scientists to gain new insights and a deeper understanding.
The size and complexity of these data sets are continuously increasing with new simulation and data acquisition methods as well as growing hardware processing power.
Visualization needs to be able scale with the data, and therefore itself needs to develop new illustration techniques in conjunction with novel approaches harness the huge processing power of parallel environments.

To accomplish this goal, I develop new approaches for the efficient usage of parallel environments (in particular GPUs and clusters) as well as the illustration of the data, with the main goal being the integration of both aspects. While the emphasis is more on one or the other depending on the specific objective, neither component may be completely neglected to achieve both expressive and responsive visualization.

The work is structured according to the emphasis of the components in three main parts as follows:
-Visualization Approaches Harnesssing Parallel Environments: The emphasis is on new visualization techniques, and GPUs and/or clusters are employed to make them responsive.
-Paralllel Visualization: Visualization approaches designed specifically for high performance in parallel environments.
-Parallel Computing Frameworks Motivated By Visualization: Generic frameworks for parallel environments targeted at application scenarios taken from common visualization approaches.

I'm currently spending more time than I should on remote rendering/visualization while writing my thesis.
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Visualization of Temporal Similarity in Field Data
S. Frey, F. Sadlo and T. Ertl
Large parts of science and engineering deal with time-dependent phenomena. We present an interactive visualization approach for detecting and exploring similarity in the temporal variation of field data. It allows the investigation of periodic and quasi-periodic behavior at single points as well as similarity between different locations within a field or between different data sets.
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Loose Capacity-Constrained Representatives for the Qualitative Visual Analysis in Molecular Dynamics
S. Frey, T. Schlömer, S. Grottel, C. Dachsbacher, O. Deussen and T. Ertl
The increasing extents of the spatial and temporal domain of molecular dynamics simulations pose a particular challenge for the visualization. Our technique replaces the huge amount of simulated particles by a smaller set of representatives that capture the characteristics of the underlying particle density and exhibit coherency over time.
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Accelerating Raycasting Utilizing Volume Segmentation of Industrial CT Data
S. Frey and T. Ertl
Raycasting large CT volumes interactively is still computationally demanding. Utilizing the segmentation information that is typically employed for object analysis, GPU ray casting can be accelerated significantly using a novel data structure that is integrated into the volume, requiring no extra texture lookups.
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Interactive High-Quality Visualization of Higher-Order Finite Elements
M. Üffinger, S. Frey, and T. Ertl
Eurographics 2010 (EG'10), Norköpping, Sweden, 2010.
Higher-order finite element methods produce complex grids which feature non-convex, curvilinear cells with varying polynomial degree. We introduce a distributed GPU-based ray casting system employing both adaptive sampling and load-balancing for achieving interactive frame rates.
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Concurrent CT Reconstruction and Visual Analysis Using Hybrid Multi-resolution Raycasting in a Cluster Environment
S. Frey, C. Müller, M. Strengert, and T. Ertl
Preparing the data for analysis after the CT scanning of an object takes a considerable amount of time. Our distributed program architecture leverages all resources of a GPU cluster for the incremental reconstruction, segmentation and rendering, provide the user with continuously updated provisional results.
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Load Balancing Utilizing Data Redundancy in Distributed Volume Rendering
S. Frey and T. Ertl
In distributed volume rendering, the cost for rendering different blocks of the volumes strongly varies with the camera configuration. Traditional load-balancing induces expensive data transfers. Our technique stores volume blocks redundantly, allowing our scheduler to evenly balance the load with almost no overhead.
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GPU-based 2D Flow Simulation Steering using Coherent Structures
M. Ament, S. Frey, F. Sadlo, T. Ertl and D. Weiskopf
The interactive investigation of CFD flow can both allow to achieve a desired flow behavior faster and supports the understanding of underlying mechanisms. We propose a CUDA-based steering system that allows interactive manipulation of boundary conditions such as obstacles or velocity profiles.
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Memory Saving Fourier Transform on GPUs
D. Kauker, H. Sanftmann, S. Frey, and T. Ertl
Current GPU Fourier transform libraries need a large buffer for storing intermediate results, severely limiting the size of an image that can be processed for instance. Our alternative two-dimensional Discrete Fourier Transform method computes the same output with far less memory by exploiting the separability property.
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CUDA-Accelerated Continuous 2-D Scatterplots
S. Bachthaler, S. Frey and D. Weiskopf
IEEE Visualization 2009 (VIS'09), Poster, Atlantic City, USA, 2009.
Continuous scatterplots represent a continous distribution function in a dense way in the scatterplot domain. We significantly speed up the original CPU approach with our GPU implementation to allow for interactive exploration.
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SIMT Microscheduling: Reducing Thread Stalling in Divergent Iterative Algorithms
S. Frey, G. Reina and T. Ertl
Current GPUs execute group of threads (warps) in lockstep. This potential leads to a large amount of wasted cycles for divergent control flow. To overcome this issue, we propose techniques to relax divergence on the fly within a computation kernel to achieve a much higher utilization of processing cores.
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PaTraCo: A Framework Enabling the Transparent and Efficient Programming of Heterogeneous Compute Networks
S. Frey and T. Ertl
In particular ad-hoc compute networks are typically heterogeneous, e.g. different classes of compute devices at different speeds suited for different kinds of tasks, varying network bandwidth). We propose a framework with a built-in scheduler that explicitly considers these characteristics and handles them transparently for the user.
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DIANA: A Device Abstraction Framework for Parallel Computations
A. Panagiotidis, D. Kauker, S. Frey, T. Ertl
There is a multitude of different APIs, SDKs and libraries for programming different many-core devices. DIANA provides a common interface to hide the complexity of managing them, allowing for easier maintainability, higher flexibility and improved portability.
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A Compute Unified System Architecture for Graphics Clusters Incorporating Data-Locality
C. Müller, S. Frey, M. Strengert, C. Dachsbacher and T. Ertl
CUDA is a parallel computing architecture for graphics cards. CUDASA logically extends its programming model and API for multi-GPU systems and distributed GPU computing. It includes an automatic GPU-accelerated scheduling mechanism that is aware of data locality to optimize GPU utilization.
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GPU-Accelerated Visualization
Ament, Marco; Frey, Steffen; Müller, Christoph; Grottel, Sebastian; Ertl, Thomas; Weiskopf, Daniel
In Book: E. W. Bethel, H. Childs, and C. Hansen: High Performance Visualization: Enabling Extreme-Scale Scientific Insight. Chapman and Hall/CRC (2012).
The book explores several distinct but interrelated approaches to high performance visualization. In my section, I give an overview on programming frameworks for GPU clusters with focus on visualization.
Advised Student Diploma Theses
  • Extraction of High Quality Isosurfaces from Large Volume Data, Thomas Mezger, 2012/13.
  • Distributed Raytracing on GPU Clusters, Jochen Puff, 2010.
  • Algorithm Design and Algorithmic-Level Optimization of Video / Image Algorithm using an Abstract Common Interface for NVIDIA CUDA and Intel Larrabee Platforms, Daniel Kauker, 2009/2010.
  • Parallel Computation of Volumetric Illumination of Astrophysical Nebulae on GPU Clusters, Manuel Moser, 2009/2010.
  • Hauptseminar Advanced Visualization Techniques, 2012/13
  • Hauptseminar Volume Rendering, 2011/12
  • Seminar Interactive Visualization Techniques, 2011
  • Hauptseminar Volume Rendering, 2010
  • Lecture Assignments Visual Computing, 2009/10
  • Lecture Assignments Image Synthesis/Rendering, 2009
  • Lecture Assignments Visual Computing, 2008/09
  • Graphics and GPU programming lab, 2008/09
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GPU-basierte Kegelstrahlrekonstruktion großer CT Datensa╠łtze
Advisiors: Magnus Strengert (VISUS), Rolf Schaller (Daimler AG)
CT reconstruction plays an important role in industrial material testing and quality control. However, this process step can take considerable time, thus delaying the overall workflow.
The work introduces and evaluates several approaches for accelerating the Feldkamp CT reconstruction algorithm using a GPU.
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Depth Peeling in OpenSceneGraph
Depth peeling extracts 2D layers of 3D geometry in depth-sorted order. I implemented this technique as final project for the Graphics and GPU programming lab. I also added some sketchy drawing outline modes to generate the look of hand-drawn sketches. It was submitted to the OpenSceneGraph project and is contained in the package as the osgdepthpeeeling example.
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Webservice-Based Remote Rendering
I was working on a web-based service for rendering medical volumetric data sets as a research assistant of Friedemann Rößler at the VIS .
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Extending a Multimedia Engine for 3d madness GmbH
3d madness is a multimedia studio, with focus on the 3D Visualization of products, buildings and data as well ass virtual reality amongst others. I was working on making a powerful open source multimedia engine (Delta3D) accessible for the 3D modelers and designers as well as integrating effects (e.g. shadows) according to their needs.