parallel coordinate plots (PCPs) are commonly used in information visualization to provide insight into multi-variate data. These plots help to spot correlations between variables. PCPs have been successfully applied ...
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In this paper, we propose a novel GPU-friendly algorithm for the Smoothed Particle Hydrodynamics (SPH) simulation for weakly compressible fluids. The major goal of our algorithm is to implement a GPU-based SPH simulat...
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visualization, interaction, and simulation (VIS) constitute a class of applications that is growing in importance. This class includes applications such as graphics rendering, video encoding, simulation, and computer ...
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ISBN:
(纸本)9781424428366
visualization, interaction, and simulation (VIS) constitute a class of applications that is growing in importance. This class includes applications such as graphics rendering, video encoding, simulation, and computer vision. These applications are ideally suited for accelerators because of their parallelizability and demand for high throughput. We compile a benchmark suite, VISBench, to sense as a proxy for this application class. We use VISBench to examine some important high level decisions for all accelerator architecture. We propose a highly parallel base architecture. We examine the need for synchronization and data communication. We also examine GPU-style SIMD execution and find that a MIMD architecture usually performs better. Given these high level choices, we use VISBench to explore the microarchitectural design space. We analyze area versus performance tradeoffs in designing individual cores and the memory hierarchy. We find that a design made of small, sample cores achieves much higher throughput than a general purpose uniprocessor. Further we find that a limited amount of support for ILP within each core aids overall performance. We find that fine-grained multithreading improves performance, but only up to a point. We find that word-level (SSE-style) SIMD provides a poor performance to area ratio. Finally, we find that sufficient memory and cache band-width is essential to performance.
parallel volume rendering is implemented and tested on an IBM Blue Gene distributed-memory parallel architecture. The goal of studying the cost of parallel rendering on a new class of supercomputers such as the Blue G...
large amounts of time-varying datasets create great challenges for users to understand and explore them. This paper proposes an efficient visualization method for observing overall data contents and changes throughout...
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ISBN:
(纸本)9781424419661
large amounts of time-varying datasets create great challenges for users to understand and explore them. This paper proposes an efficient visualization method for observing overall data contents and changes throughout an entire time-varying dataset. We develop an interactive storyboard approach by composing sample volume renderings and descriptive geometric primitives that are generated through data analysis processes. Our storyboard system integrates automatic visualization generation methods and interactive adjustment procedures to provide new tools for visualizing and exploring time-varying datasets. We also provide a flexible framework to quantify data differences and automatically select representative datasets through exploring scientific data distribution features. Since this approach reduces the visualized data amount into a more understandable size and format for users, it can be used to effectively visualize, represent, and explore a large time-varying dataset. Initial user study results show that our approach shortens the exploration time and reduces the number of datasets that users visualized individually. This visualization method is especially useful for situations that require close observance or are not capable of interactive rendering, such as documentation and demonstration.
The widespread use of mobile devices brings opportunities to capture large-scale, continuous information about human behavior. Mobile data has tremendous value, leading to business opportunities, market strategies, se...
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Animation is frequently utilized to visually depict change in time-varying data sets. For this task, it is a natural fit. Yet explicit animation is rarely employed for static data. We discuss the use of animation to o...
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ISBN:
(纸本)9781424419661
Animation is frequently utilized to visually depict change in time-varying data sets. For this task, it is a natural fit. Yet explicit animation is rarely employed for static data. We discuss the use of animation to overcome three common limitations faced by information visualization applications in the context of small-display devices: constraints on the output display, limited interaction possibilities, and high data density. We provide concrete examples of applying animation to combat such limitations for four common visualization types: geo-spatial data, treemaps, parallel coordinate displays, and large graphs. Unlike previous work which examines animation for maintaining user orientation during view changes or for displaying data variables, we discuss animation's utility for multiplexing available screen space. In the context of constrained displays, we demonstrate its ability to effectively gain screen resolution, to quickly uncover trends, to help find unexpected data patterns, and to reduce visual clutter.
We present the Zoomable Adjacency Matrix Explorer (ZAME), a visualization tool for exploring graphs at a scale of millions of nodes and edges. ZAME is based on an adjacency matrix graph representation aggregated at mu...
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ISBN:
(纸本)9781424419661
We present the Zoomable Adjacency Matrix Explorer (ZAME), a visualization tool for exploring graphs at a scale of millions of nodes and edges. ZAME is based on an adjacency matrix graph representation aggregated at multiple scales. It allows analysts to explore a graph at many levels, zooming and panning with interactive performance from an overview to the most detailed views. Several components work together in the ZAME tool to make this possible. Efficient matrix ordering algorithms group related elements. Individual data cases are aggregated into higher-order meta-representations. Aggregates are arranged into a pyramid hierarchy that allows for on-demand paging to GPU shader programs to support smooth multiscale browsing. Using ZAME, we are able to explore the entire French Wikipedia-over 500,000 articles and 6,000,000 links-with interactive performance on standard consumer-level computer hardware.
In this paper, we consider the interaction between application programmers and tools that automatically search a space of application-level parameters that are believed to impact the performance of an application sign...
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ISBN:
(纸本)9781424416936
In this paper, we consider the interaction between application programmers and tools that automatically search a space of application-level parameters that are believed to impact the performance of an application significantly. We study performance tuning of a large scientific application, the visualization component of a molecular dynamics simulation. The key contribution of the approach is the use of high-level programmer-specified models of the expected performance behavior of individual parameters. We use these models to reduce the search space associated with the range of parameter values and achieve results that perform close to that of a more exhaustive search of the parameter space. With this case study, we show the importance of appropriate parameter selection, with the difference between best-case and worst-case performance with a particular input data set and processor configuration of up to a factor of 17. We show that through the use of models, we can drastically reduce search time, examining only 0.3% to 5% of the search space, and usually select an implementation that is close to the best performance, within 0.84% to 15%, even though the models are not completely accurate.
The recent advances in high performance computing, storage and networking technologies have enabled fundamental changes in current climate research. While sharing datasets and results is already common practice in cli...
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ISBN:
(纸本)9781424422487
The recent advances in high performance computing, storage and networking technologies have enabled fundamental changes in current climate research. While sharing datasets and results is already common practice in climate modeling, direct sharing of the analysis and visualization process is also becoming feasible. We report our efforts to develop a capability, coupled with the Earth System Grid (ESG), for sharing an entire executable workspace of visualization among collaborators. Evolutionary history of visualizations of research findings can also be captured and shared The data intensive nature of the visualization system requires using several advanced techniques of visualization and parallel computing. With visualization clients implemented through standard web browsers, however, the ensuing complexity is made transparent to end-users. We demonstrate the efficacy of our system using cutting edge climate datasets.
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