Practical parallel rendering of detailed neuron simulations

Parallel rendering of large polygonal models with transparency is challenging due to the need for alpha-correct blending and compositing, which is costly for very large models with high depth complexity and spatial overlap. In this paper we compare the performance of raster-based rendering methods on mesh models of neurons using two applications, one of which is specifically tailored to the neuroscience application domain, the other a general purpose visualization tool with domain specific additions. The first implements both sort-first and sort-last and uses a scene graph style traversal to cull objects, and dual depth peeling for order independent transparency, whilst the other uses a simpler brute force data-parallel approach with sort last composition. The advantages and trade offs of these approaches are discussed. We present the optimized algorithms needed to achieve interactive frame rates for a non-trivial, real-world parallel rendering scenario. We show that a generic data visualization application can provide competitive performance when optimizing its rendering pipeline, with some loss of capability over an optimized domain-specific application.

Published in:
EGPGV '13 Proceedings of the 13th Eurographics Symposium on Parallel Graphics and Visualization, 49-56
Presented at:
13th Eurographics Symposium on Parallel Graphics and Visualization, Girona, Spain, May 4-5, 2013
Aire-la-Ville, Switzerland, Eurographics Association

 Record created 2016-02-15, last modified 2018-01-28

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