Hybrid Image-/Data-Parallel Rendering Using Island Parallelism

Stefan Zellmann, Ingo Wald, Joao Barbosa, Serkan Demirci, Alper Sahistan, Ugur Gudukbay

View presentation: 2022-10-16T15:45:00Z GMT-0600 Change your timezone on the schedule page
2022-10-16T15:45:00Z
Exemplar figure, described by caption below
Four very different data-parallel, ray-based renderers. a) Sort-last absorption + emission volume renderer. b) Ray- forwarding production path tracer realized using OptiX and hardware ray tracing. c) Volumetric path tracer optimized for scientific visualization (sci-vis). d) Large unstructured element-marcher with simulation-provided bounding geometry. All four renderers operate on huge data, but have largely different scaling properties; we show how hybrid image-/data-parallel rendering with islands can benefit these renderers to scale far beyond either image or data-parallel rendering applied in isolation.

The live footage of the talk, including the Q&A, can be viewed on the session page, LDAV: Parallelization & Progressiveness.

Abstract

In parallel ray tracing, techniques fall into one of two camps: image-parallel techniques aim at increasing frame rate by replicating scene data across nodes and splitting the rendering work across different ranks, and data-parallel techniques aim at increasing the size of the model that can be rendered by splitting the model across multiple ranks, but typically cannot scale much in frame rate. We propose and evaluate a hybrid approach that combines the advantages of both by splitting a set of N × M ranks into M islands of N ranks each and using data-parallel rendering within each island and image parallelism across islands. We discuss the integration of this concept into four wildly different parallel renderers and evaluate the efficacy of this approach based on multiple different data sets.