Hernando, Juan B.Biddiscombe, JohnBohara, BidurEilemann, StefanSchürmann, FelixFabio Marton and Kenneth Moreland2014-01-262014-01-262013978-3-905674-45-31727-348Xhttps://doi.org/10.2312/EGPGV/EGPGV13/049-056Parallel 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.I.3.m [Computer Graphics]MiscellaneousParallel Rendering Computer Applications [J.3]Life and Medical SciencesBiology and genetics