A GPU‐Adapted Structure for Unstructured Grids

A key advantage of working with structured grids (e.g., images) is the ability to directly tap into the powerful machinery of linear algebra. This is not much so for unstructured grids where intermediate bookkeeping data structures stand in the way. On modern high performance computing hardware, the...

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Veröffentlicht in:	Computer graphics forum 2017-05, Vol.36 (2), p.495-507
Hauptverfasser:	Zayer, Rhaleb, Steinberger, Markus, Seidel, Hans‐Peter
Format:	Artikel
Sprache:	eng
Schlagworte:	Categories and Subject Descriptors (according to ACM CCS) Computer graphics Computer memory Computer peripherals Data structures Finite element method G.1.0 [Mathematics of Computing]: General—Parallel algorithms G.1.3 [Mathematics of Computing]: Numerical Linear Algebra — Sparse, structured, and very large systems Graphics processing units Hardware I.3.1 [Computer Graphics]: Hardware Architecture—Graphics processors I.3.5 [Computer Graphics]: Computational Geometry and Object Modeling—Geometric algorithms, languages, and systems I.3.6 [Computer Graphics]: Methodology and Techniques — Graphics data structures and data types Linear algebra Machinery and equipment Mathematical analysis Matrix algebra Matrix methods Matrix representation Multiplication Sparsity Structured grids (mathematics) Unstructured grids (mathematics) Vector processing (computers)
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