一個適合分群組延遲光追蹤的平行運算資料結構

An Efficient Data Structure for Clustered Deferred Ray Tracing

牛明韋(Ming-Wei Niu)

指導教授 ： 施仁忠

國立交通大學/資訊學院/多媒體工程研究所/碩士(2018年)

摘要

像空間光追蹤結合了圖形渲染管線化與路徑追蹤的優勢，通常擁有兩個階段。第一個階段為使用渲染管線化去建構透視投影空間下的資料結構，第二個階段為路徑追蹤中的過程走訪這個資料結構。為了達到即時渲染需要完全平行演算法。原本DRIT 演算法只能在NVIDIA 的Maxwell 架構上執行，我們擴展其可攜性。
我們引入了分群組延遲光追蹤演算法，利用群組化資料結構取代分塊化資料結構以達到擴增原始演算法可執行的圖形處理器。此方法延續了延遲基於圖像光追蹤的大部的特性，亦保持渲染管線化與光追蹤的連結性。

關鍵字

光追蹤 ； 分群組著色 ； 延遲著色

並列摘要

Screen-space ray tracing combines both advantages of graphics rasterization pipeline and path tracing. This usually consists of two stages, building and tracing. The first stage is building data structures (DS) in the perspective space. The second stage is tracing the primitives walkthrough by the ray. Fully paralleled algorithm on graphics processing unit (GPU) is essential to accelerate the building DS stage.
We introduce a scheme called clustered deferred ray tracing (CDRT), replacing the tiled buckets with clustered buckets. Our method extends deferred image-based ray tracing (DIRT) which has strong continuum between rasterization and ray-tracing approaches for fully dynamic scenes. Originally, the algorithm can only run on NVIDIA Maxwell architecture. We replace the tiled DS to clustered DS. This framework is portable on general GPUs and keeps most of the features in DIRT.

並列關鍵字

ray tracing ； clustered shading ； deferred shading

參考文獻

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