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VisPy: Harnessing The GPU For Fast, High-Level Visualization

Luke Campagnola 1 Almar Klein 2 Eric Larson 3 Cyrille Rossant 4 Nicolas P. Rougier 5, 6, 7
1 UNC - University of North Carolina [Chapel Hill]
2 University of Twente [Netherlands]
3 University of Washington [Seattle]
4 APMN - Audition (Psychophysique, Modélisation, Neurosciences)
LSP - Laboratoire des systèmes perceptifs
5 Mnemosyne - Mnemonic Synergy
LaBRI - Laboratoire Bordelais de Recherche en Informatique, Inria Bordeaux - Sud-Ouest, IMN - Institut des Maladies Neurodégénératives [Bordeaux]
6 IMN - Institut des Maladies Neurodégénératives [Bordeaux]
7 LaBRI - Laboratoire Bordelais de Recherche en Informatique
Abstract : The growing availability of large, multidimensional data sets has created demand for high-performance, interactive visualization tools. VisPy leverages the GPU to provide fast, interactive, and beautiful visualizations in a high-level API. Here we introduce the main features, architecture, and techniques used in VisPy.
Keywords : interactive visualization plotting performance graphics opengl python
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https://hal.inria.fr/hal-01208191
Contributor : Nicolas P. Rougier <>
Submitted on : Tuesday, October 6, 2015 - 11:25:25 AM
Last modification on : Tuesday, September 22, 2020 - 3:46:52 AM
Long-term archiving on: : Thursday, January 7, 2016 - 10:13:24 AM

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Luke Campagnola, Almar Klein, Eric Larson, Cyrille Rossant, Nicolas P. Rougier. VisPy: Harnessing The GPU For Fast, High-Level Visualization. Proceedings of the 14th Python in Science Conference, Jul 2015, Austin, Texas, United States. ⟨hal-01208191⟩

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