000 | 04086nam a22005535i 4500 | ||
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001 | 978-3-031-02604-1 | ||
003 | DE-He213 | ||
005 | 20240730164012.0 | ||
007 | cr nn 008mamaa | ||
008 | 220601s2017 sz | s |||| 0|eng d | ||
020 |
_a9783031026041 _9978-3-031-02604-1 |
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024 | 7 |
_a10.1007/978-3-031-02604-1 _2doi |
|
050 | 4 | _aQA76.9.I52 | |
072 | 7 |
_aUYZF _2bicssc |
|
072 | 7 |
_aMAT013000 _2bisacsh |
|
072 | 7 |
_aUYZF _2thema |
|
082 | 0 | 4 |
_a001.4226 _223 |
100 | 1 |
_aFalk, Martin. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _981594 |
|
245 | 1 | 0 |
_aInteractive GPU-based Visualization of Large Dynamic Particle Data _h[electronic resource] / _cby Martin Falk, Sebastian Grottel, Michael Krone, Guido Reina. |
250 | _a1st ed. 2017. | ||
264 | 1 |
_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2017. |
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300 |
_aXII, 109 p. _bonline resource. |
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336 |
_atext _btxt _2rdacontent |
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337 |
_acomputer _bc _2rdamedia |
||
338 |
_aonline resource _bcr _2rdacarrier |
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347 |
_atext file _bPDF _2rda |
||
490 | 1 |
_aSynthesis Lectures on Visualization, _x2159-5178 |
|
505 | 0 | _aAcknowledgments -- Figure Credits -- Introduction -- History -- GPU-based Glyph Ray Casting -- Acceleration Strategies -- Data Structures -- Efficient Nearest Neighbor Search on the GPU -- Improved Visual Quality -- Application-driven Abstractions -- Summary and Outlook -- Bibliography -- Authors' Biographies. | |
520 | _aPrevalent types of data in scientific visualization are volumetric data, vector field data, and particle-based data. Particle data typically originates from measurements and simulations in various fields, such as life sciences or physics. The particles are often visualized directly, that is, by simple representants like spheres. Interactive rendering facilitates the exploration and visual analysis of the data. With increasing data set sizes in terms of particle numbers, interactive high-quality visualization is a challenging task. This is especially true for dynamic data or abstract representations that are based on the raw particle data. This book covers direct particle visualization using simple glyphs as well as abstractions that are application-driven such as clustering and aggregation. It targets visualization researchers and developers who are interested in visualization techniques for large, dynamic particle-based data. Its explanations focus on GPU-accelerated algorithms for high-performance rendering and data processing that run in real-time on modern desktop hardware. Consequently, the implementation of said algorithms and the required data structures to make use of the capabilities of modern graphics APIs are discussed in detail. Furthermore, it covers GPU-accelerated methods for the generation of application-dependent abstract representations. This includes various representations commonly used in application areas such as structural biology, systems biology, thermodynamics, and astrophysics. | ||
650 | 0 |
_aInformation visualization. _914255 |
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650 | 0 |
_aData structures (Computer science). _98188 |
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650 | 0 |
_aInformation theory. _914256 |
|
650 | 0 |
_aData mining. _93907 |
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650 | 1 | 4 |
_aData and Information Visualization. _933848 |
650 | 2 | 4 |
_aData Structures and Information Theory. _931923 |
650 | 2 | 4 |
_aData Mining and Knowledge Discovery. _981595 |
700 | 1 |
_aGrottel, Sebastian. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _981596 |
|
700 | 1 |
_aKrone, Michael. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _981597 |
|
700 | 1 |
_aReina, Guido. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _981598 |
|
710 | 2 |
_aSpringerLink (Online service) _981599 |
|
773 | 0 | _tSpringer Nature eBook | |
776 | 0 | 8 |
_iPrinted edition: _z9783031014765 |
776 | 0 | 8 |
_iPrinted edition: _z9783031037320 |
830 | 0 |
_aSynthesis Lectures on Visualization, _x2159-5178 _981600 |
|
856 | 4 | 0 | _uhttps://doi.org/10.1007/978-3-031-02604-1 |
912 | _aZDB-2-SXSC | ||
942 | _cEBK | ||
999 |
_c85206 _d85206 |