Guest Speaker

Speaker: Michael Sedlmair

 
Title: Visual Analysis of In-car Communication Networks

Abstract:

Modern cars contain a wide spectrum of functionality, which is implemented by many interconnected electronic control units (ECUs). Overlooking all details of these increasingly complex in-car communication networks is a major challenge for developers. In our work, we have designed a number of analysis tools for in-car communication networks to enable developers to trace errors better and faster. By observing current working practices of automotive analysis experts, we found that the tools in use are mostly text-based and often fail to provide sufficient insight into correlations and overview aspects. They lack sophisticated visualization, navigation and data reduction techniques. Our research goal is to find novel and adapt existing methods of visual analytics (VA) and information visualization (InfoVis) to support the process of analyzing in-car communication networks. With a set of prototypes and their evaluation, we managed to provide concrete solutions and verify how in-car communication analysis can benefit form research in VA and InfoVis.

Speaker: Hans-Christian Hege

 
Title: Uncertain Isocontours

Abstract

Almost all scientific data is affected by uncertainty. Visualization techniques that consider uncertainties therefore are urgently needed. In this talk I will focus on scalar fields as input data. For analysis of such fields, usually topological or geometrical features are extracted and displayed. The most prominent features in scalar fields are isocontours. A means to describe how errors in the input data are amplified during feature extraction is numerical condition. Applying this to isocontours, the sensitivity of isocontours to changes in the input data can be computed and displayed. Furthermore, the average condition number can aid the selection of isovalues that correspond to isocontours that are particularly robust.

Speaker: Dr. Mario Costa Sousa

 
Title: Scalable Visualization in Oil/Gas Reservoir Exploration & Production

Abstract

Oil and gas reservoir Exploration and Production (E&P) involve complex tasks, datasets and workflows from three main groups of inter-related disciplines: geophysics, geology and reservoir & production engineering. Visualization technology has been a key component of the increased success and efficiency across these disciplines and in all states of the field development cycle. Advances in the fields of scientific visualization, computer graphics, human-computer interaction and high-performance computing have enabled a significantly large range of reservoir visualization tasks. Today, visualization technology in oil/gas reservoir E&P faces great challenges due to the intersection of these advances with higher level of access to data application and integration, increasingly large and complex datasets, higher-degrees of uncertainty, and multi disciplinary collaborative decision-making.

Distinguished speaker series: Professor Michael Unser

 

Title: Beyond the digital divide - Ten good reasons for using splines

Abstract

"Think analog, act digital" is a motto that is relevant to scientific computing and algorithm design in a variety of disciplines, including numerical analysis, image/signal processing, and computer graphics. Here, we will argue that cardinal splines constitute a theoretical and computational framework that is ideally matched to this philosophy, especially when the data is available on a uniform grid. We show that multidimensional spline interpolation or approximation can be performed most efficiently using recursive digital filtering techniques.

Distinguished speaker series: Professor Pat Hanrahan

 
  
Title: Why are Graphics Systems so Fast?

Abstract

Over the last decade graphics hardware has become a key component of mobile and personal computers. Most programmers understand CPUs well, but have a limited understanding of GPUs (Graphics Processing Units). GPUs are viewed as specialized hardware optimized for rendering. That view is not accurate. Instead, they are best characterized as parallel computers that combine many cores, many threads, and wide vector processing units. In this talk, I will describe the architectures of different GPUs built by AMD, NVIDIA and Intel (the new Larrabee processor). I will also discuss the programming models that are used to achieve high performance on such heterogeneous architectures. The innovative combination of processor design and programming model are why graphics systems are so fast.

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