In exploratory scientific visualization, isosurfaces are typically created with an explicit polygonal representation for the surface using a technique such as Marching Cubes. For even moderate data sets, Marching Cube...
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Object-order rendering techniques present an attractive approach to run-time visualization of structured grid data, particularly when combined with a parallel rendering paradigm such as image composition. The ability ...
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ISBN:
(纸本)1581132379
Object-order rendering techniques present an attractive approach to run-time visualization of structured grid data, particularly when combined with a parallel rendering paradigm such as image composition. The ability of this combination to exploit hardware exceeds that of parallel image order methods. However, certain configurations of grid boundaries prevent composition from being performed correctly. In particular, when the boundary between two partitions contains concave sections, the partitions may no longer be depth sorted correctly, a requirement for some visualization techniques such as direct volume rendering. This occurs because the concave boundary prevents even the simple ordering of two adjacent partitions. If the data may be repartitioned such that it can be depth sorted correctly, then an image composition approach is a viable option. To facilitate such an operation, we present an algorithm to analyze the geometric structure of a grid boundary and extract knowledge about how the boundary impacts depth sorting and therefore image composition. We then show through examples how this knowledge may be applied to create a set of partitions that may be properly depth sorted.
The interactive visualization and exploration of large scientific data sets is a challenging and difficult task;their size often far exceeds the performance and memory capacity of even the most powerful graphics works...
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A methodology intended to avoid bottlenecks that typically arise as the result of data consumers that must access and process large amounts of data that has been generated and resides on other hosts, and which must pa...
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A methodology intended to avoid bottlenecks that typically arise as the result of data consumers that must access and process large amounts of data that has been generated and resides on other hosts, and which must pass through a central data cache prior to being used by the data consumer is described. It is based on a fundamental paradigm that the end result rendered by a data consumer can be produced using a reduced data set that has been distilled or filtered from the original data set. data distribution bottlenecks for visualization applications are reduced by avoiding the transfer of large amounts of raw data in favor of considerably distilled visual data.
The limitations of serial processors for managing large computationally intensive dataset problems in fields such as visualization and geographical information systems (GIS) are well known. parallel processing techniq...
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作者:
Frederick, P.Gattass, M.Mediano, M.R.TeCGraf
Grupo de Tecnologia em Computação Gráfica Departamento de Informática PUC-Rio Rua Marquěs de São Vicente 225 Rio de Janeiro RJ22453-900 Brazil
The use of appropriate data structures for storing sets of graphical objects can lead to great performance improvements in the visualization of large figures, such as maps and CAD drawings. We present a study on the p...
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We introduce a scheme for static analysis that allows us to partition large geometric datasets at multiple levels of granularity to achieve both load balancing in parallel computations and minimal access to secondary ...
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We introduce a scheme for static analysis that allows us to partition large geometric datasets at multiple levels of granularity to achieve both load balancing in parallel computations and minimal access to secondary memory in out-of-core computations. The idea is illustrated and fully exploited for the case of isosurface extraction, but extendible to a class of algorithms based on a small set of parameters and for which an appropriate static analysis can be performed.
parallelising ray tracing with a dataparallel approach allows rendering of arbitrarily large models, but the inherent load imbalances may lead to severe inefficiencies. To compensate for the uneven load distribution,...
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parallelising ray tracing with a dataparallel approach allows rendering of arbitrarily large models, but the inherent load imbalances may lead to severe inefficiencies. To compensate for the uneven load distribution, demand-driven tasks may be split off and scheduled to processors that are less busy. We propose a hybrid scheduling algorithm which brings tasks and data together according to coherence between rays. The amount of demand-driven versus dataparallel tasks is a function of the coherence between rays and the amount of imbalance in the basic data-parallel load. Processing power, communication and memory are three resources which should be evenly used. Our current implementation is assessed against these requirements, showing good scalability and very little communication at the cost of a slightly larger memory overhead.
This paper reports the performance of a parallel volume rendering algorithm for visualizing a large-scale unstructured-grid dataset produced by a three-dimensional aerodynamics simulation. This dataset, containing ove...
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ISBN:
(纸本)0780359011
This paper reports the performance of a parallel volume rendering algorithm for visualizing a large-scale unstructured-grid dataset produced by a three-dimensional aerodynamics simulation. This dataset, containing over 18 million tetrahedra, allows us to extend our performance results to a problem which is more than 30 times larger than the one we examined previously. This high resolution dataset also allows us to see fine, three-dimensional features in the flow field. All our tests were performed on the SGI/Cray T3E operated by NASA's Goddard Space Flight Center. Using 511 processors, a rendering rate of almost 9 million tetrahedra/second was achieved with a parallel overhead of 26%.
This paper proposes a new parallel ray-casting scheme for very large volume data on distributed-memory architectures. Our method, based on data compression, attempts to enhance the speedup of parallel rendering by qui...
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